mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 00:21:07 +01:00
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/10528 adding 2 features to core and model_helper - reroute_tensor which supports op insertion on net level - model_helper complete net and cut net used for full graph analysis Differential Revision: D9330345 fbshipit-source-id: 56341d3f500e72069ee306e20266c8590ae7985a
50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
"""unittest for ModelHelper class"""
|
|
|
|
from __future__ import absolute_import, division, print_function
|
|
|
|
import unittest
|
|
|
|
from caffe2.python import brew, model_helper
|
|
|
|
|
|
class ModelHelperTest(unittest.TestCase):
|
|
def test_get_complete_net(self):
|
|
model = model_helper.ModelHelper("test_orig")
|
|
conv = brew.conv(
|
|
model,
|
|
"input",
|
|
"conv",
|
|
dim_in=3,
|
|
dim_out=16,
|
|
weight_init=("MSRAFill", {}),
|
|
kernel=3,
|
|
stride=1,
|
|
pad=0,
|
|
)
|
|
conv = brew.spatial_bn(model, conv, "conv_bn", 16, epsilon=1e-3, is_test=False)
|
|
conv = brew.relu(model, conv, "conv_relu")
|
|
pred = brew.fc(model, conv, "pred", dim_in=16 * 3 * 3, dim_out=10)
|
|
brew.softmax(model, pred, "softmax")
|
|
net = model.GetCompleteNet()
|
|
model2 = model_helper.ModelHelper("test_new")
|
|
model2.ConstructInitTrainNetfromNet(net)
|
|
|
|
net = model.param_init_net
|
|
net2 = model2.param_init_net
|
|
for op1, op2 in zip(net.Proto().op, net2.Proto().op):
|
|
op1.debug_info = op1.debug_info + "/param_init_net"
|
|
self.assertEqual(
|
|
op1, op2, "op mismatch between {}\n and {}\n".format(op1, op2)
|
|
)
|
|
net = model.net
|
|
net2 = model2.net
|
|
for op1, op2 in zip(net.Proto().op, net2.Proto().op):
|
|
self.assertEqual(
|
|
op1, op2, "op mismatch between {}\n and {}\n".format(op1, op2)
|
|
)
|
|
# this is not guaranteed in other situations where user define own net
|
|
self.assertEqual(
|
|
sorted(map(str, net.external_inputs)),
|
|
sorted(map(str, net2.external_inputs)),
|
|
)
|