aboutsummaryrefslogtreecommitdiffstats
path: root/simulation/vi_blocks.py
diff options
context:
space:
mode:
Diffstat (limited to 'simulation/vi_blocks.py')
-rw-r--r--simulation/vi_blocks.py18
1 files changed, 10 insertions, 8 deletions
diff --git a/simulation/vi_blocks.py b/simulation/vi_blocks.py
index 5deb6f6..50c7fb1 100644
--- a/simulation/vi_blocks.py
+++ b/simulation/vi_blocks.py
@@ -52,16 +52,17 @@ def create_vi_model(n_nodes, n_samp=100):
if __name__ == "__main__":
batch_size = 100
- frequency = 10
+ freq = 10
+ graph = utils.create_wheel(1000)
n_samples = 50
- graph = utils.create_random_graph(n_nodes=10)
+ #graph = utils.create_random_graph(n_nodes=10)
print('GRAPH:\n', graph, '\n-------------\n')
x, s, mu, sig, cost = create_vi_model(len(graph), n_samples)
rmse = ub.rmse_error(graph, mu)
step_rules = algorithms.CompositeRule([algorithms.AdaDelta(),
- ClippedParams(1e-3, 1 - 1e-3)])
+ ClippedParams(1e-3, 1000)])
alg = algorithms.GradientDescent(cost=cost, parameters=[mu, sig],
step_rule=step_rules)
@@ -70,11 +71,12 @@ if __name__ == "__main__":
alg, data_stream,
log_backend="sqlite",
extensions=[
- be.FinishAfter(after_n_batches=10**4),
- bm.TrainingDataMonitoring([cost, rmse, mu], every_n_batches=frequency),
- be.Printing(every_n_batches=frequency, after_epoch=False),
- ub.JSONDump("logs/tmp.json", every_n_batches=10),
- #ub.ActiveLearning(dataset=data_stream.dataset, params=graph)
+ be.FinishAfter(after_n_batches=10**3),
+ bm.TrainingDataMonitoring([cost, rmse, mu], every_n_batches=freq),
+ be.Printing(every_n_batches=freq, after_epoch=False),
+ ub.JSONDump("logs/nonactive_vi.json", every_n_batches=freq),
+ #ub.ActiveLearning(dataset=data_stream.dataset, params=graph,
+ #every_n_batches=freq)
]
)
loop.run()