changing active learning definition plus main loops of mle/vi_blocks

3 files changed, 19 insertions, 21 deletions

diff --git a/simulation/mle_blocks.py b/simulation/mle_blocks.py
index ab8816f..0d27869 100644
--- a/simulation/mle_blocks.py
+++ b/simulation/mle_blocks.py
@@ -30,8 +30,9 @@ def create_mle_model(graph):
 
 if __name__ == "__main__":
     batch_size = 100
-    n_obs = 100000
-    graph = utils.create_wheel(100)
+    #n_obs = 100000
+    freq = 10
+    graph = utils.create_wheel(1000)
 
     print('GRAPH:\n', graph, '\n-------------\n')
 
@@ -51,10 +52,10 @@ if __name__ == "__main__":
         extensions=[
             be.FinishAfter(after_n_batches=10**3),
             bm.TrainingDataMonitoring([cost, params,
-                                       rmse, error], every_n_batches=10),
-            be.Printing(every_n_batches=10),
-            ub.JSONDump("log.json", every_n_batches=10),
-            ub.ActiveLearning(data_stream.dataset),
+                                       rmse, error], every_n_batches=freq),
+            be.Printing(every_n_batches=freq),
+            ub.JSONDump("logs/active_outdegree_mle.json", every_n_batches=freq),
+            ub.ActiveLearning(data_stream.dataset, graph, every_n_batches=freq),
         ],
     )
     loop.run()
diff --git a/simulation/utils_blocks.py b/simulation/utils_blocks.py
index 3b29972..72a6881 100644
--- a/simulation/utils_blocks.py
+++ b/simulation/utils_blocks.py
@@ -31,16 +31,14 @@ class ActiveLearning(be.SimpleExtension):
     Extension which updates the node_p array passed to the get_data method of
     LearnedDataset
     """
-    def __init__(self, dataset, **kwargs):
+    def __init__(self, dataset, params, **kwargs):
         super(ActiveLearning, self).__init__(**kwargs)
         self.dataset = dataset
+        self.params = params
 
     def do(self, which_callback, *args):
-        out_degree = np.sum(self.dataset.graph, axis=1)
-        self.dataset.node_p = out_degree / np.sum(out_degree)
-
-#    def do(self, which_callback, *args):
-
+        exp_out_par = np.exp(np.sum(self.params, axis=1))
+        self.dataset.node_p = exp_out_par / np.sum(exp_out_par)
 
 
 class JSONDump(be.SimpleExtension):
diff --git a/simulation/vi_blocks.py b/simulation/vi_blocks.py
index b78375b..5deb6f6 100644
--- a/simulation/vi_blocks.py
+++ b/simulation/vi_blocks.py
@@ -51,10 +51,10 @@ def create_vi_model(n_nodes, n_samp=100):
 
 
 if __name__ == "__main__":
-    n_cascades = 10000
-    batch_size = 10
+    batch_size = 100
+    frequency = 10
     n_samples = 50
-    graph = utils.create_random_graph(n_nodes=4)
+    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)
@@ -65,17 +65,16 @@ if __name__ == "__main__":
 
     alg = algorithms.GradientDescent(cost=cost, parameters=[mu, sig],
                                      step_rule=step_rules)
-    data_stream = ub.fixed_data_stream(n_cascades, graph, batch_size,
-                                       shuffle=False)
-    # data_stream = ub.dynamic_data_stream(graph, batch_size)
+    data_stream = ub.dynamic_data_stream(graph, batch_size)
     loop = main_loop.MainLoop(
         alg, data_stream,
         log_backend="sqlite",
         extensions=[
             be.FinishAfter(after_n_batches=10**4),
-            bm.TrainingDataMonitoring([cost, mu, sig, rmse],
-                                      every_n_batches=10),
-            be.Printing(every_n_batches=100, after_epoch=False),
+            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)
         ]
     )
     loop.run()