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add benckmark

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This commit is contained in:
WenmuZhou
2022-07-30 10:00:11 +08:00
parent f6250d61e4
commit dd1e17fd79
28 changed files with 425 additions and 59 deletions
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tools/program.py
+27 -10
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@@ -154,6 +154,24 @@ def check_xpu(use_xpu):
except Exception as e:
pass
def to_float32(preds):
if isinstance(preds, dict):
for k in preds:
if isinstance(preds[k], dict) or isinstance(preds[k], list):
preds[k] = to_float32(preds[k])
else:
preds[k] = preds[k].astype(paddle.float32)
elif isinstance(preds, list):
for k in range(len(preds)):
if isinstance(preds[k], dict):
preds[k] = to_float32(preds[k])
elif isinstance(preds[k], list):
preds[k] = to_float32(preds[k])
else:
preds[k] = preds[k].astype(paddle.float32)
else:
preds = preds.astype(paddle.float32)
return preds
def train(config,
train_dataloader,
@@ -252,13 +270,19 @@ def train(config,
# use amp
if scaler:
with paddle.amp.auto_cast():
with paddle.amp.auto_cast(level='O2'):
if model_type == 'table' or extra_input:
preds = model(images, data=batch[1:])
elif model_type in ["kie", 'vqa']:
preds = model(batch)
else:
preds = model(images)
preds = to_float32(preds)
loss = loss_class(preds, batch)
avg_loss = loss['loss']
scaled_avg_loss = scaler.scale(avg_loss)
scaled_avg_loss.backward()
scaler.minimize(optimizer, scaled_avg_loss)
else:
if model_type == 'table' or extra_input:
preds = model(images, data=batch[1:])
@@ -266,15 +290,8 @@ def train(config,
preds = model(batch)
else:
preds = model(images)
loss = loss_class(preds, batch)
avg_loss = loss['loss']
if scaler:
scaled_avg_loss = scaler.scale(avg_loss)
scaled_avg_loss.backward()
scaler.minimize(optimizer, scaled_avg_loss)
else:
loss = loss_class(preds, batch)
avg_loss = loss['loss']
avg_loss.backward()
optimizer.step()
optimizer.clear_grad()