In [17]:

    

import pickle


    

In [18]:

    

file = "/home/galvan/development/RNNs/models/temporal_order_plain, min_length: 150_14_multi_diag/results.pkl"
data = pickle.load(open(file, "rb"))


    

In [19]:

    

data = sorted(data, key=lambda d: d['n_iters'])
print("n_rows:{}".format(len(data)))


    

    




n_rows:24

In [20]:

    

data[0]


    

    
Out[20]:





{'clip_thr': 0.7, 'id': 3, 'lr': 0.001, 'n_iters': 55000, 'std_dev': 0.05}

In [21]:

    

data[1]


    

    
Out[21]:





{'clip_thr': 0.7, 'id': 21, 'lr': 0.01, 'n_iters': 80800, 'std_dev': 0.05}

In [22]:

    

data[2]


    

    
Out[22]:





{'clip_thr': 1, 'id': 5, 'lr': 0.001, 'n_iters': 81400, 'std_dev': 0.05}

In [23]:

    

data[3]


    

    
Out[23]:





{'clip_thr': 1, 'id': 23, 'lr': 0.01, 'n_iters': 101000, 'std_dev': 0.05}

In [24]:

    

data[4]


    

    
Out[24]:





{'clip_thr': 1, 'id': 17, 'lr': 0.005, 'n_iters': 104400, 'std_dev': 0.05}

In [25]:

    

data[5]


    

    
Out[25]:





{'clip_thr': 1, 'id': 22, 'lr': 0.01, 'n_iters': 126600, 'std_dev': 0.01}

In [ ]: