a
    nɀj                     @   sd   d Z ddlZddlZddlmZ ddlZddlmZ ddl	m
Z
 dd ZdddZedkr`e  dS )aB  Run a policy (or a scripted action) and write a replay for the three.js bench.

  python rollout.py --policy ../runs/<run>/policy_best.json --out ../bench/replays/latest.json

The replay carries world poses per body, so the viewer needs no kinematics of
its own: it just moves the meshes it built from the same spec file.
    N)Path)RobotEnv)Policyc                  C   s  t  } | jdd d | jdd dd | jdd dd | jdtttjjd	 d | jd
tdd | jdtdd | jdtddd | jddd | jddd | jdtdd dd | 	 }|j
rt|j
nd }|jp|r|jdnd }|stttjjd }|jp$|r"|jdnd }|r:|jddnd }t||j|||jrVd!nd d"}tj|j}| }|jrt|jd#std$|jd%tj|jtd&|j_d'd( |j_t||||j |j|j!|j" |j
d)}	t|j#}
|
jj$d*d*d+ t%|
d,}t&'|	| W d    n1 s(0    Y  |	d- }|d. rTd/|d0  d1nd2|d0  d1}|d3 rrd4nd5}t(|
 d6|j d7| | d8|d9  d:t)|	d;  d< d S )=Nz--spec)defaultz--policyzomit for a zero-action fall)r   helpz--taskzincentive to run underz--outzbench/replays/latest.jsonz	--seconds      (@)typer   z--seed{   z--fps2   zreplay frame rate)r   r   r   z--no-dr
store_true)actionz--stochasticz--cmd   z.fix the command to vx wz instead of resampling)r   nargsr   r   speczrobots/wheeled_biped.jsontask
obs_layoutlegacyunionF)seedr   layout	randomisecmdz--cmd does not apply to the z
 incentive)dtypec                  _   s   d S )N )akr   r   +/home/ghrups/robot-bench/trainer/rollout.py<lambda>5       zmain.<locals>.<lambda>)secondsr   fpsdeterministicpolicy_pathT)parentsexist_okwsummaryfellzFELL at 
survived_ssz	survived successz SUCCESS z  [z] z	  reward total_rewardz  framesz frames)*argparseArgumentParseradd_argumentstrr   __file__parentfloatint
parse_argspolicyr   loadr   metagetr   r   r   no_drnprandomdefault_rngresetr   hasattrtask_obj
SystemExit	task_namearrayon_steprecordr   r    Z
stochasticoutmkdiropenjsondumpprintlen)apargsr7   	spec_pathr   r   envrngobsreplayrG   fr)   Zverdictokr   r   r   main   s\    

,*
rW   r   r
   Tc	                 C   s  t j|}	t|| j }
tdttd| | j }|  g}g g g g g g g g d}d}d}t|
D ]d}|r|j	|d |	|d\}}}t 
|d dd}nt | j}| |\}}}}}||7 }|| dkr||   |d	 t| jd
 |d t|d d |d t|d d |d t|d
 t| jdd}|d tt|d d
 |d tt|d d
 |d dd |D  |d dd | jjD  |rft| jd} qqfdd | j D }t| jd j|| j| jj| j| jd |||  t|| j d| j| j dd | jD dd | jdg D |||dur`|n
t| jd|dut|d|d t | j!dt | j"| d d!S )"zRun one episode and return a replay dict.

    Shared by the CLI and by the trainer's periodic snapshots, so a snapshot
    taken mid-training is byte-compatible with a replay produced by hand.
       g      ?)theightup_zrewardcmd_vxcmd_wzr   tau        N)r!   r   rY      rZ      r[   r\   r   )r`   r`   r]   r^   r   c                 S   s   g | ]}t t|d qS )rb   roundr4   .0vr   r   r   
<listcomp>l   r   zrecord.<locals>.<listcomp>r_   c                 S   s   g | ]}t t|d qS rc   rd   rf   r   r   r   ri   n   r   r   c                 S   s   i | ]\}}|d kr||qS )_pathr   )rg   r   rh   r   r   r   
<dictcomp>x   r   zrecord.<locals>.<dictcomp>rk   c                 S   s   g | ]}t t|d qS rj   rd   )rg   xr   r   r   ri      r   c                 S   s   g | ]}|d  qS )namer   )rg   r   r   r   r   ri      r   	actuatorsenabled)r(   r'   r,   stepsZ
randomisedr*   )r   Z	spec_jsonr   Z
task_labelpropsrP   r7   steps_trainedbodiesdt	episode_s	tau_limitro   r-   seriesr&   )#r<   r=   r>   r5   
control_dtmaxre   framerangeactclipzerosact_dimstepappendrY   getattrrA   r4   dataactuator_forcer   itemsr   rn   rC   labelrr   
body_names	max_stepsrw   r:   booldrr*   )rQ   r7   rS   r   r   r    r!   r"   rs   rR   Zn_stepsZeveryr-   rx   totalZfell_atir   _rr'   truncinfor   Z	spec_copyr   r   r   rF   G   sl    

rF   __main__)r   r   r
   TNN)__doc__r.   rJ   pathlibr   numpyr<   rQ   r   ppor   rW   rF   __name__r   r   r   r   <module>   s   4  
N