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refactor hyperband implementation

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René Knaebel
2017-09-29 22:59:57 +02:00
parent 090c89a127
commit 605447440f
4 changed files with 81 additions and 47 deletions
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5
models/__init__.py
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@@ -17,7 +17,6 @@ def get_models_by_params(params: dict):
dropout = params.get("dropout")
# mainly prediction model
flow_features = params.get("flow_features")
domain_features = params.get("domain_features")
window_size = params.get("window_size")
domain_length = params.get("domain_length")
filter_main = params.get("filter_main")
@@ -36,10 +35,10 @@ def get_models_by_params(params: dict):
embedding_model = networks.get_embedding(embedding_size, input_length, filter_embedding, kernel_embedding,
hidden_embedding, 0.5)
old_model = networks.get_model(0.25, flow_features, domain_features, window_size, domain_length,
old_model = networks.get_model(0.25, flow_features, hidden_embedding, window_size, domain_length,
filter_main, kernel_main, dense_dim, embedding_model, model_output)
new_model = networks.get_new_model(0.25, flow_features, domain_features, window_size, domain_length,
new_model = networks.get_new_model(0.25, flow_features, hidden_embedding, window_size, domain_length,
filter_main, kernel_main, dense_dim, embedding_model, model_output)
return embedding_model, old_model, new_model