Allow for multiple example inputs when creating summary (#543)

This commit is contained in:
VSJMilewski 2019-12-09 13:42:07 +01:00 committed by William Falcon
parent b492e2b89e
commit d562172b4c
1 changed files with 16 additions and 5 deletions

View File

@ -50,20 +50,31 @@ class ModelSummary(object):
input_ = self.model.example_input_array
if self.model.on_gpu:
input_ = input_.cuda(0)
device = next(self.model.parameters()).get_device()
# test if input is a list or a tuple
if isinstance(input_, (list, tuple)):
input_ = [input_i.cuda(device) if torch.is_tensor(input_i) else input_i
for input_i in input_]
else:
input_ = input_.cuda(device)
if self.model.trainer.use_amp:
input_ = input_.half()
# test if it is not a list or a tuple
if isinstance(input_, (list, tuple)):
input_ = [input_i.half() if torch.is_tensor(input_i) else input_i
for input_i in input_]
else:
input_ = input_.half()
with torch.no_grad():
for _, m in mods:
if type(input_) is list or type(input_) is tuple: # pragma: no cover
if isinstance(input_, (list, tuple)): # pragma: no cover
out = m(*input_)
else:
out = m(input_)
if type(input_) is tuple or type(input_) is list: # pragma: no cover
if isinstance(input_, (list, tuple)): # pragma: no cover
in_size = []
for x in input_:
if type(x) is list:
@ -75,7 +86,7 @@ class ModelSummary(object):
in_sizes.append(in_size)
if type(out) is tuple or type(out) is list: # pragma: no cover
if isinstance(out, (list, tuple)): # pragma: no cover
out_size = np.asarray([x.size() for x in out])
else:
out_size = np.array(out.size())