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[pycaffe] basic, partial testing of Net and SGDSolver
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longjon committed Dec 31, 2014
1 parent 9a335e9 commit 6b9cbe0
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77 changes: 77 additions & 0 deletions python/caffe/test/test_net.py
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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)
49 changes: 49 additions & 0 deletions python/caffe/test/test_solver.py
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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()

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