def test_CloneLayer():
node = mdp.nodes.PCANode(input_dim=10, output_dim=5)
x = numx_rand.random([10, 70]).astype('f')
layer = mh.CloneLayer(node, 7)
layer.train(x)
y = layer.execute(x)
assert layer.dtype == numx.dtype('f')
assert y.dtype == layer.dtype
def test_SFA_net(noisenode):
sfa_node = mdp.nodes.SFANode(input_dim=20 * 20, output_dim=10, dtype='f')
switchboard = mh.Rectangular2dSwitchboard(in_channels_xy=100,
field_channels_xy=20,
field_spacing_xy=10)
flownode = mh.FlowNode(mdp.Flow([noisenode, sfa_node]))
sfa_layer = mh.CloneLayer(flownode, switchboard.output_channels)
flow = mdp.Flow([switchboard, sfa_layer])
train_gen = numx.cast['f'](numx_rand.random((3, 10, 100 * 100)))
flow.train([None, train_gen])
def testHiNetHTML(noisenode):
# create some flow for testing
sfa_node = mdp.nodes.SFANode(input_dim=20 * 20, output_dim=10)
switchboard = mh.Rectangular2dSwitchboard(in_channels_xy=100,
field_channels_xy=20,
field_spacing_xy=10)
flownode = mh.FlowNode(mdp.Flow([noisenode, sfa_node]))
sfa_layer = mh.CloneLayer(flownode, switchboard.output_channels)
flow = mdp.Flow([switchboard, sfa_layer])
# create dummy file to write the HTML representation
html_file = io.StringIO()
hinet_html = mdp.hinet.HiNetHTMLVisitor(html_file)
hinet_html.convert_flow(flow)
html_file.close()
def test_hinet_simple_net():
switchboard = mh.Rectangular2dSwitchboard(in_channels_xy=(12, 8),
field_channels_xy=4,
field_spacing_xy=2,
in_channel_dim=3)
node = mdp.nodes.PCANode(input_dim=4 * 4 * 3, output_dim=5)
flownode = mh.FlowNode(mdp.Flow([
node,
]))
layer = mh.CloneLayer(flownode, switchboard.output_channels)
flow = mdp.Flow([switchboard, layer])
x = numx_rand.random([5, switchboard.input_dim])
flow.train(x)
