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Fix seq2seq time calculation #4875

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Merged
merged 2 commits into from
Sep 25, 2020
Merged

Fix seq2seq time calculation #4875

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3decc74
add tokens per sec; test=develop
phlrain Sep 23, 2020
7c61a13
Merge branch 'develop' of https://github.com/PaddlePaddle/models into…
phlrain Sep 23, 2020
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24 changes: 16 additions & 8 deletions PaddleNLP/seq2seq/seq2seq/train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -97,8 +97,7 @@ def main():
dropout=dropout)
loss = model.build_graph()
inference_program = train_program.clone(for_test=True)
clip=fluid.clip.GradientClipByGlobalNorm(
clip_norm=max_grad_norm)
clip = fluid.clip.GradientClipByGlobalNorm(clip_norm=max_grad_norm)
lr = args.learning_rate
opt_type = args.optimizer
if opt_type == "sgd":
Expand Down Expand Up @@ -190,8 +189,10 @@ def train():
total_loss = 0
word_count = 0.0
batch_times = []
time_interval = 0.0
batch_start_time = time.time()
epoch_word_count = 0.0
for batch_id, batch in enumerate(train_data_iter):
batch_start_time = time.time()
input_data_feed, word_num = prepare_input(
batch, epoch_id=epoch_id)
word_count += word_num
Expand All @@ -206,27 +207,34 @@ def train():
batch_end_time = time.time()
batch_time = batch_end_time - batch_start_time
batch_times.append(batch_time)
time_interval += batch_time
epoch_word_count += word_num

if batch_id > 0 and batch_id % 100 == 0:
print("-- Epoch:[%d]; Batch:[%d]; Time: %.5f s; ppl: %.5f" %
(epoch_id, batch_id, batch_time,
np.exp(total_loss / word_count)))
print(
"-- Epoch:[%d]; Batch:[%d]; Time: %.5f s; ppl: %.5f; speed: %0.5f tokens/sec"
% (epoch_id, batch_id, batch_time,
np.exp(total_loss / word_count),
word_count / time_interval))
ce_ppl.append(np.exp(total_loss / word_count))
total_loss = 0.0
word_count = 0.0
time_interval = 0.0

# profiler tools
if args.profile and epoch_id == 0 and batch_id == 100:
profiler.reset_profiler()
elif args.profile and epoch_id == 0 and batch_id == 105:
return
batch_start_time = time.time()

end_time = time.time()
epoch_time = end_time - start_time
ce_time.append(epoch_time)
print(
"\nTrain epoch:[%d]; Epoch Time: %.5f; avg_time: %.5f s/step\n"
% (epoch_id, epoch_time, sum(batch_times) / len(batch_times)))
"\nTrain epoch:[%d]; Epoch Time: %.5f; avg_time: %.5f s/step; speed: %0.5f tokens/sec\n"
% (epoch_id, epoch_time, sum(batch_times) / len(batch_times),
epoch_word_count / sum(batch_times)))

if not args.profile:
save_path = os.path.join(args.model_path,
Expand Down