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| { | |
| "agent": "DQNAgent", | |
| "episodes": 10000, | |
| "max_timesteps": 10000, | |
| "preprocessing": [ | |
| { | |
| "type": "image_resize", | |
| "width": 84, | |
| "height": 84 |
Islandman93
/ nips_dqn_architecture.json
Created
August 5, 2017 13:45
TensorForce configuration for the NIPS DQN architecture
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| [ | |
| { | |
| "type": "conv2d", | |
| "size": 16, | |
| "window": 8, | |
| "stride": 4, | |
| "bias": true, | |
| "padding": "VALID" | |
| }, | |
| { |
Islandman93
/ batch_dqn_agent_visual.json
Created
August 5, 2017 13:39
TensorForce config for batch dqn agent
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| "preprocessing": [ | |
| { | |
| "type": "image_resize", | |
| "width": 84, | |
| "height": 84 | |
| }, | |
| { | |
| "type": "grayscale" | |
| }, |
Islandman93
/ spatial_pyramid_pooling.py
Created
December 2, 2015 22:26
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| class SPPLayer(lasagne.layers.Layer): | |
| def __init__(self, incoming, **kwargs): | |
| super(SPPLayer, self).__init__(incoming, **kwargs) | |
| # divide by 4 gives 16 patches | |
| self.win1 = (int(np.floor(incoming.output_shape[2]/4.0)), int(np.floor(incoming.output_shape[3]/4.0))) | |
| self.str1 = (int(np.ceil(incoming.output_shape[2]/4.0)), int(np.ceil(incoming.output_shape[3]/4.0))) | |
| # divide by 2 gives 4 patches | |
| self.win2 = (int(np.floor(incoming.output_shape[2]/2.0)), int(np.floor(incoming.output_shape[3]/2.0))) |