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Update SuperMLP

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D-X-Y
2021-03-19 23:57:23 +08:00
parent 31b8122cc1
commit 0c56a729ad
13 changed files with 412 additions and 85 deletions
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23
tests/test_super_model.py
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@@ -30,32 +30,37 @@ class TestSuperLinear(unittest.TestCase):
print(model.super_run_type)
self.assertTrue(model.bias)
inputs = torch.rand(32, 10)
inputs = torch.rand(20, 10)
print("Input shape: {:}".format(inputs.shape))
print("Weight shape: {:}".format(model._super_weight.shape))
print("Bias shape: {:}".format(model._super_bias.shape))
outputs = model(inputs)
self.assertEqual(tuple(outputs.shape), (32, 36))
self.assertEqual(tuple(outputs.shape), (20, 36))
abstract_space = model.abstract_search_space
abstract_space.clean_last()
abstract_child = abstract_space.random()
print("The abstract searc space:\n{:}".format(abstract_space))
print("The abstract child program:\n{:}".format(abstract_child))
model.set_super_run_type(super_core.SuperRunMode.Candidate)
model.apply_candiate(abstract_child)
model.apply_candidate(abstract_child)
output_shape = (32, abstract_child["_out_features"].value)
output_shape = (20, abstract_child["_out_features"].value)
outputs = model(inputs)
self.assertEqual(tuple(outputs.shape), output_shape)
def test_super_mlp(self):
hidden_features = spaces.Categorical(12, 24, 36)
out_features = spaces.Categorical(12, 24, 36)
out_features = spaces.Categorical(24, 36, 48)
mlp = super_core.SuperMLP(10, hidden_features, out_features)
print(mlp)
self.assertTrue(mlp.fc1._out_features, mlp.fc2._in_features)
inputs = torch.rand(4, 10)
outputs = mlp(inputs)
self.assertEqual(tuple(outputs.shape), (4, 48))
abstract_space = mlp.abstract_search_space
print("The abstract search space for SuperMLP is:\n{:}".format(abstract_space))
self.assertEqual(
@@ -67,10 +72,16 @@ class TestSuperLinear(unittest.TestCase):
is abstract_space["fc2"]["_in_features"]
)
abstract_space.clean_last_sample()
abstract_space.clean_last()
abstract_child = abstract_space.random(reuse_last=True)
print("The abstract child program is:\n{:}".format(abstract_child))
self.assertEqual(
abstract_child["fc1"]["_out_features"].value,
abstract_child["fc2"]["_in_features"].value,
)
mlp.set_super_run_type(super_core.SuperRunMode.Candidate)
mlp.apply_candidate(abstract_child)
outputs = mlp(inputs)
output_shape = (4, abstract_child["fc2"]["_out_features"].value)
self.assertEqual(tuple(outputs.shape), output_shape)