Python Assistant.get_cropped_sample Examples

Example #1

if weights_file != -1:
    ActorCritic.load_state_dict(torch.load(weights_file))

# set up assistant
Assistant = Assistant(directory=DIRECTORY, number_of_images=700)

##### SET UP TRAINING #####
##### SET UP TRAINING #####
##### SET UP TRAINING #####

for iteration in range(300000):
    # zero the graph gradient
    ActorCritic.zero_grad()

    # get a cropped image sample
    image = Assistant.get_cropped_sample()[0].unsqueeze(0).unsqueeze(0).to(
        device)

    # pass image through first module of FasteNet and get feature map
    F_map_1 = FasteNet.module_one(image)

    # based on feature map, scale to get inputs for AC
    AC_input = F.adaptive_max_pool2d(F_map_1[..., :32], 32)

    # based on feature map get reward and actions
    actions, estimated_reward = ActorCritic.forward(AC_input)

    # crop the feature map
    cropped_F_map = Assistant.crop_feature_map(actions[0].squeeze().item(),
                                               actions[1].squeeze().item(),
                                               F_map_1).to(device)