diff options
Diffstat (limited to 'simulation/utils_blocks.py')
| -rw-r--r-- | simulation/utils_blocks.py | 31 |
1 files changed, 0 insertions, 31 deletions
diff --git a/simulation/utils_blocks.py b/simulation/utils_blocks.py index 0d30786..3b29972 100644 --- a/simulation/utils_blocks.py +++ b/simulation/utils_blocks.py @@ -121,34 +121,3 @@ def dynamic_data_stream(graph, batch_size): data_set = LearnedDataset(node_p, graph) scheme = fuel.schemes.ConstantScheme(batch_size) return fuel.streams.DataStream(dataset=data_set, iteration_scheme=scheme) - - -if __name__ == "__main__": - batch_size = 100 - n_obs = 1000 - frequency = 1 - graph = utils.create_wheel(1000) - print('GRAPH:\n', graph, '\n-------------\n') - - g_shared = theano.shared(value=graph, name='graph') - x, s, params, cost = create_mle_model(graph) - rmse = rmse_error(g_shared, params) - error = relative_error(g_shared, params) - - alg = algorithms.GradientDescent( - cost=-cost, parameters=[params], step_rule=blocks.algorithms.AdaDelta() - ) - data_stream = create_learned_data_stream(graph, batch_size) - #data_stream = create_fixed_data_stream(n_obs, graph, batch_size) - loop = main_loop.MainLoop( - alg, data_stream, - extensions=[ - be.FinishAfter(after_n_batches=10**4), - bm.TrainingDataMonitoring([cost, rmse, error], - every_n_batches=frequency), - be.Printing(every_n_batches=frequency), - JSONDump("tmpactive_log.json", every_n_batches=frequency), - ActiveLearning(data_stream.dataset, every_n_batches=frequency) - ], - ) - loop.run() |