def test_fc(self):
m, n, k = (15, 15, 15)
X = np.random.rand(m, k).astype(np.float32) - 0.5
workspace.FeedBlob("x", X)
model = ModelHelper(name="test_model")
out = brew.fc(model, "x", "out_1", k, n)
out = brew.packed_fc(model, out, "out_2", n, n)
out = brew.fc_decomp(model, out, "out_3", n, n)
out = brew.fc_prune(model, out, "out_4", n, n)
workspace.RunNetOnce(model.param_init_net)
workspace.RunNetOnce(model.net)
def FC_Prune(self, *args, **kwargs):
return brew.fc_prune(self, *args, **kwargs)
def FC_Prune(self, *args, **kwargs):
return brew.fc_prune(self, *args, **kwargs)