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Merge branch 'dygraph' into dygraph_for_srn

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This commit is contained in:
xiaoting
2021-01-29 11:37:19 +08:00
committed by GitHub
parent f214437538 fad40158b0
commit 6ebbbfe46c
49 changed files with 350 additions and 141 deletions
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tools/program.py
+14 -14
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@@ -218,7 +218,7 @@ def train(config,
stats['lr'] = lr
train_stats.update(stats)
if cal_metric_during_train: # onlt rec and cls need
if cal_metric_during_train: # only rec and cls need
batch = [item.numpy() for item in batch]
post_result = post_process_class(preds, batch[1])
eval_class(post_result, batch)
@@ -253,19 +253,19 @@ def train(config,
Model_Average.apply()
cur_metirc = eval(model, valid_dataloader, post_process_class,
eval_class)
cur_metirc_str = 'cur metirc, {}'.format(', '.join(
['{}: {}'.format(k, v) for k, v in cur_metirc.items()]))
logger.info(cur_metirc_str)
cur_metric_str = 'cur metric, {}'.format(', '.join(
['{}: {}'.format(k, v) for k, v in cur_metric.items()]))
logger.info(cur_metric_str)
# logger metric
if vdl_writer is not None:
for k, v in cur_metirc.items():
for k, v in cur_metric.items():
if isinstance(v, (float, int)):
vdl_writer.add_scalar('EVAL/{}'.format(k),
cur_metirc[k], global_step)
if cur_metirc[main_indicator] >= best_model_dict[
cur_metric[k], global_step)
if cur_metric[main_indicator] >= best_model_dict[
main_indicator]:
best_model_dict.update(cur_metirc)
best_model_dict.update(cur_metric)
best_model_dict['best_epoch'] = epoch
save_model(
model,
@@ -276,7 +276,7 @@ def train(config,
prefix='best_accuracy',
best_model_dict=best_model_dict,
epoch=epoch)
best_str = 'best metirc, {}'.format(', '.join([
best_str = 'best metric, {}'.format(', '.join([
'{}: {}'.format(k, v) for k, v in best_model_dict.items()
]))
logger.info(best_str)
@@ -308,7 +308,7 @@ def train(config,
prefix='iter_epoch_{}'.format(epoch),
best_model_dict=best_model_dict,
epoch=epoch)
best_str = 'best metirc, {}'.format(', '.join(
best_str = 'best metric, {}'.format(', '.join(
['{}: {}'.format(k, v) for k, v in best_model_dict.items()]))
logger.info(best_str)
if dist.get_rank() == 0 and vdl_writer is not None:
@@ -338,13 +338,13 @@ def eval(model, valid_dataloader, post_process_class, eval_class):
eval_class(post_result, batch)
pbar.update(1)
total_frame += len(images)
# Get final metirc，eg. acc or hmean
metirc = eval_class.get_metric()
# Get final metric，eg. acc or hmean
metric = eval_class.get_metric()
pbar.close()
model.train()
metirc['fps'] = total_frame / total_time
return metirc
metric['fps'] = total_frame / total_time
return metric
def preprocess(is_train=False):