Function get_config

examples/SimilarityLearning/mnist-embeddings.py:339–359

(model, algorithm_name)

def get_config(model, algorithm_name):

    extra_display = ["cost"]
    if not algorithm_name == "cosine" and not algorithm_name == "center":
        extra_display = extra_display + ["loss/pos-dist", "loss/neg-dist"]

    return TrainConfig(
        dataflow=model.get_data(),
        model=model(),
        callbacks=[
            ModelSaver(),
            ScheduledHyperParamSetter('learning_rate', [(10, 1e-5), (20, 1e-6)])
        ],
        extra_callbacks=[
            MovingAverageSummary(),
            ProgressBar(extra_display),
            MergeAllSummaries(),
            RunUpdateOps()
        ],
        max_epoch=20,
    )


def visualize(model_path, model, algo_name):