--- /dev/null
+import unittest
+import tempfile
+import os
+import numpy as np
+
+import caffe
+
+def simple_net_file(num_output):
+ """Make a simple net prototxt, based on test_net.cpp, returning the name
+ of the (temporary) file."""
+
+ f = tempfile.NamedTemporaryFile(delete=False)
+ f.write("""name: 'testnet' force_backward: true
+ layers { type: DUMMY_DATA name: 'data' top: 'data' top: 'label'
+ dummy_data_param { num: 5 channels: 2 height: 3 width: 4
+ num: 5 channels: 1 height: 1 width: 1
+ data_filler { type: 'gaussian' std: 1 }
+ data_filler { type: 'constant' } } }
+ layers { type: CONVOLUTION name: 'conv' bottom: 'data' top: 'conv'
+ convolution_param { num_output: 11 kernel_size: 2 pad: 3
+ weight_filler { type: 'gaussian' std: 1 }
+ bias_filler { type: 'constant' value: 2 } }
+ weight_decay: 1 weight_decay: 0 }
+ layers { type: INNER_PRODUCT name: 'ip' bottom: 'conv' top: 'ip'
+ inner_product_param { num_output: """ + str(num_output) + """
+ weight_filler { type: 'gaussian' std: 2.5 }
+ bias_filler { type: 'constant' value: -3 } } }
+ layers { type: SOFTMAX_LOSS name: 'loss' bottom: 'ip' bottom: 'label'
+ top: 'loss' }""")
+ f.close()
+ return f.name
+
+class TestNet(unittest.TestCase):
+ def setUp(self):
+ self.num_output = 13
+ net_file = simple_net_file(self.num_output)
+ self.net = caffe.Net(net_file)
+ # fill in valid labels
+ self.net.blobs['label'].data[...] = \
+ np.random.randint(self.num_output,
+ size=self.net.blobs['label'].data.shape)
+ os.remove(net_file)
+
+ def test_memory(self):
+ """Check that holding onto blob data beyond the life of a Net is OK"""
+
+ params = sum(map(list, self.net.params.itervalues()), [])
+ blobs = self.net.blobs.values()
+ del self.net
+
+ # now sum everything (forcing all memory to be read)
+ total = 0
+ for p in params:
+ total += p.data.sum() + p.diff.sum()
+ for bl in blobs:
+ total += bl.data.sum() + bl.diff.sum()
+
+ def test_forward_backward(self):
+ self.net.forward()
+ self.net.backward()
+
+ def test_inputs_outputs(self):
+ self.assertEqual(self.net.inputs, [])
+ self.assertEqual(self.net.outputs, ['loss'])
+
+ def test_save_and_read(self):
+ f = tempfile.NamedTemporaryFile(delete=False)
+ f.close()
+ self.net.save(f.name)
+ net_file = simple_net_file(self.num_output)
+ net2 = caffe.Net(net_file, f.name)
+ os.remove(net_file)
+ os.remove(f.name)
+ for name in self.net.params:
+ for i in range(len(self.net.params[name])):
+ self.assertEqual(abs(self.net.params[name][i].data
+ - net2.params[name][i].data).sum(), 0)
--- /dev/null
+import unittest
+import tempfile
+import os
+import numpy as np
+
+import caffe
+from test_net import simple_net_file
+
+class TestSolver(unittest.TestCase):
+ def setUp(self):
+ self.num_output = 13
+ net_f = simple_net_file(self.num_output)
+ f = tempfile.NamedTemporaryFile(delete=False)
+ f.write("""net: '""" + net_f + """'
+ test_iter: 10 test_interval: 10 base_lr: 0.01 momentum: 0.9
+ weight_decay: 0.0005 lr_policy: 'inv' gamma: 0.0001 power: 0.75
+ display: 100 max_iter: 100 snapshot_after_train: false""")
+ f.close()
+ self.solver = caffe.SGDSolver(f.name)
+ self.solver.net.set_mode_cpu()
+ # fill in valid labels
+ self.solver.net.blobs['label'].data[...] = \
+ np.random.randint(self.num_output,
+ size=self.solver.net.blobs['label'].data.shape)
+ self.solver.test_nets[0].blobs['label'].data[...] = \
+ np.random.randint(self.num_output,
+ size=self.solver.test_nets[0].blobs['label'].data.shape)
+ os.remove(f.name)
+ os.remove(net_f)
+
+ def test_solve(self):
+ self.assertEqual(self.solver.iter, 0)
+ self.solver.solve()
+ self.assertEqual(self.solver.iter, 100)
+
+ def test_net_memory(self):
+ """Check that nets survive after the solver is destroyed."""
+
+ nets = [self.solver.net] + list(self.solver.test_nets)
+ self.assertEqual(len(nets), 2)
+ del self.solver
+
+ total = 0
+ for net in nets:
+ for ps in net.params.itervalues():
+ for p in ps:
+ total += p.data.sum() + p.diff.sum()
+ for bl in net.blobs.itervalues():
+ total += bl.data.sum() + bl.diff.sum()