work around a pylint & astroid bug
This commit is contained in:
		
							parent
							
								
									794418d29f
								
							
						
					
					
						commit
						d71c131e5b
					
				|  | @ -4,10 +4,13 @@ | ||||||
| # Copyright (c) 2017-18, Carnegie Mellon University Database Group | # Copyright (c) 2017-18, Carnegie Mellon University Database Group | ||||||
| # | # | ||||||
| 
 | 
 | ||||||
|  | 
 | ||||||
|  | import imp | ||||||
| import random | import random | ||||||
| import os | import os | ||||||
| import sys | import sys | ||||||
| try: | try: | ||||||
|  |     imp.find_module('matplotlib.pyplot') | ||||||
|     import matplotlib.pyplot as plt |     import matplotlib.pyplot as plt | ||||||
| except (ModuleNotFoundError, ImportError): | except (ModuleNotFoundError, ImportError): | ||||||
|     plt = None |     plt = None | ||||||
|  | @ -111,7 +114,7 @@ def plotlines(x_axis, data1, data2, label1, label2, title, path): | ||||||
|         plt.clf() |         plt.clf() | ||||||
| 
 | 
 | ||||||
| 
 | 
 | ||||||
| def main(knob_dim=192, metric_dim=60, lr=0.001, mode=0, n_loops=1000): | def main(knob_dim=8, metric_dim=60, lr=0.0001, mode=2, n_loops=2000): | ||||||
|     if not plt: |     if not plt: | ||||||
|         LOG.info("Cannot import matplotlib. Will write results to files instead of figures.") |         LOG.info("Cannot import matplotlib. Will write results to files instead of figures.") | ||||||
|     random.seed(0) |     random.seed(0) | ||||||
|  | @ -119,7 +122,7 @@ def main(knob_dim=192, metric_dim=60, lr=0.001, mode=0, n_loops=1000): | ||||||
|     torch.manual_seed(0) |     torch.manual_seed(0) | ||||||
|     env = Environment(knob_dim, metric_dim, mode=mode) |     env = Environment(knob_dim, metric_dim, mode=mode) | ||||||
| 
 | 
 | ||||||
|     n_repeats = 5 |     n_repeats = 10 | ||||||
|     for i in range(n_repeats): |     for i in range(n_repeats): | ||||||
|         if i == 0: |         if i == 0: | ||||||
|             results1, x_axis = train_ddpg(env, gamma=0, lr=lr, n_loops=n_loops) |             results1, x_axis = train_ddpg(env, gamma=0, lr=lr, n_loops=n_loops) | ||||||
|  |  | ||||||
		Loading…
	
		Reference in New Issue