def test_prune_module(self):
conv = MaskConv2d(32, 32, 3)
G = 4
prune_utils.prune_module(conv, G)
self.assertFalse(torch.allclose(conv.mask,
torch.ones(conv.mask.shape)))
def prune_module(self,
name,
mod,
*args,
g_cfg=None,
fake_mask=False,
**kwargs):
""" Prune a single module.
We expect that after pruning, the mask in mod can be
updated to a pruned result.
Args:
name(str): name of the module
mod(MaskConv2d): the module to be pruned.
"""
# TODO maybe not pass by kwargs
G = self.args.num_groups
if g_cfg is not None and name in g_cfg:
G = g_cfg[name]["G"]
# do some verification
W = model_utils.get_weight_parameter(mod)
F, C = W.shape[:2]
assert F == g_cfg[name]["F"] and C == g_cfg[name]["C"]
if fake_mask and isinstance(mod, MaskConv2d):
mod.fake_mask = True
prune_utils.prune_module(mod, G=G, MCPG=self.args.mcpg, **kwargs)
def prune_module(self, name, mod, G, **kwargs):
""" Prune a specific module.
NOTE: G is known at this moment.
"""
assert isinstance(mod, MaskConv2d)
assert G >= 1, "{} has G={} smaller than 1".format(name, G)
W = model_utils.get_weight_parameter(mod)
C_out, C_in = W.shape[:2]
if G == 1 or (C_out % G != 0 or C_in % G != 0):
# NOTE: we return if this module cannot be pruned
return
prune_utils.prune_module(mod, G=G, **kwargs)