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When I try to train the model on a kaggle by running
python arnold.py
--freedoom "true" # use freedoom resources
--height 60 # screen height
--width 108 # screen width
--gray "false" # use grayscale screen
--use_screen_buffer "true" # use the screen buffer (what the player sees)
--use_depth_buffer "false" # use the depth buffer
--labels_mapping "" # use extra feature maps for specific objects
--game_features "target,enemy" # game features prediction (auxiliary tasks)
--render_hud "false" # render the HUD (status bar in the bottom of the screen)
--render_crosshair "true" # render crosshair (targeting aid in the center of the screen)
--render_weapon "true" # render weapon
--hist_size 4 # history size
--frame_skip 4 # frame skip (1 = keep every frame)
--action_combinations "attack+move_lr;turn_lr;move_fb" # agent allowed actions
--freelook "false" # allow the agent to look up and down
--speed "on" # make the agent run
--crouch "off" # make the agent crouch
--batch_size 32 # batch size
--replay_memory_size 1000000 # maximum number of frames in the replay memory
--start_decay 0 # epsilon decay iteration start
--stop_decay 1000000 # epsilon decay iteration end
--final_decay 0.1 # final epsilon value
--gamma 0.99 # discount factor gamma
--dueling_network "false" # use a dueling architecture
--clip_delta 1.0 # clip the delta loss
--update_frequency 4 # DQN update frequency
--dropout 0.5 # dropout on CNN output layer
--optimizer "rmsprop,lr=0.0002" # network optimizer
--network_type "dqn_rnn" # network type (dqn_ff / dqn_rnn)
--recurrence "lstm" # recurrent network type (rnn / gru / lstm)
--n_rec_layers 1 # number of layers in the recurrent network
--n_rec_updates 5 # number of updates by sample
--remember 1 # remember all frames during evaluation
--use_bn "off" # use BatchNorm when processing the screen
--variable_dim "32" # game variables embeddings dimension
--bucket_size "[10, 1]" # bucket game variables (typically health / ammo)
--hidden_dim 512 # hidden layers dimension
--scenario "deathmatch" # scenario
--wad "full_deathmatch" # WAD file (scenario file)
--map_ids_train "2,3,4,5" # maps to train the model
--map_ids_test "6,7,8" # maps to test the model
--n_bots 8 # number of enemy bots
--randomize_textures "true" # randomize walls / floors / ceils textures during training
--init_bots_health 20 # reduce initial life of enemy bots (helps a lot when using pistol)
--exp_name new_train # experiment name
--dump_freq 200000 # periodically dump the model
--gpu_id -1
I get the following Error
Can someone help me fix this
The text was updated successfully, but these errors were encountered:
When I try to train the model on a kaggle by running
I get the following Error
Can someone help me fix this
The text was updated successfully, but these errors were encountered: