huangfu/InteractionImitation
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making expert data save s, a, sp. making dataloader also load batches thisway. renaming state to ego_state. converting path_x and path_y to single path variable. making number of samples for ray an argument. adjusting metrics, policy, and other functions to be able to handle this

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Arec
2021-08-04 09:45:36 -07:00
parent 7ae01f73a2
commit f9729b0a9d
7 changed files with 89 additions and 70 deletions
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6
src/metrics.py
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@@ -37,7 +37,7 @@ def metrics(filestr: str, test_dataset, policy):
info['average_velocity'] = avg_v
# convert policy dtype between float32 and float64
policy.policy = policy.policy.type(test_dataset[0]['state'].dtype)
policy.policy = policy.policy.type(test_dataset[0]['state']['ego_state'].dtype)
# generate actions in test dataset
true_actions, pred_actions = [], []
@@ -45,9 +45,9 @@ def metrics(filestr: str, test_dataset, policy):
test_loader = DataLoader(test_dataset, batch_size=1024)
with torch.no_grad():
for (batch_idx, batch) in enumerate(test_loader):
pred_actions.append(policy(batch))
pred_actions.append(policy(batch['state']))
true_actions.append(batch['action'])
true_velocities.append(batch['state'][:,2])
true_velocities.append(batch['state']['ego_state'][:,2])
true_actions, pred_actions = torch.cat(true_actions,dim=0), torch.cat(pred_actions, dim=0)
visualize_distribution(true_actions[:,0], pred_actions[:,0], filestr+'_action_viz')