80 lines
2.7 KiB
Python
80 lines
2.7 KiB
Python
import numpy as np
|
|
import tensorflow as tf
|
|
from baselines.ppo2.policies import nature_cnn
|
|
from baselines.a2c.utils import fc, batch_to_seq, seq_to_batch, lstm, sample
|
|
|
|
|
|
class AcerCnnPolicy(object):
|
|
|
|
def __init__(self, sess, ob_space, ac_space, nenv, nsteps, nstack, reuse=False):
|
|
nbatch = nenv * nsteps
|
|
nh, nw, nc = ob_space.shape
|
|
ob_shape = (nbatch, nh, nw, nc * nstack)
|
|
nact = ac_space.n
|
|
X = tf.placeholder(tf.uint8, ob_shape) # obs
|
|
with tf.variable_scope("model", reuse=reuse):
|
|
h = nature_cnn(X)
|
|
pi_logits = fc(h, 'pi', nact, init_scale=0.01)
|
|
pi = tf.nn.softmax(pi_logits)
|
|
q = fc(h, 'q', nact)
|
|
|
|
a = sample(pi_logits) # could change this to use self.pi instead
|
|
self.initial_state = [] # not stateful
|
|
self.X = X
|
|
self.pi = pi # actual policy params now
|
|
self.q = q
|
|
|
|
def step(ob, *args, **kwargs):
|
|
# returns actions, mus, states
|
|
a0, pi0 = sess.run([a, pi], {X: ob})
|
|
return a0, pi0, [] # dummy state
|
|
|
|
def out(ob, *args, **kwargs):
|
|
pi0, q0 = sess.run([pi, q], {X: ob})
|
|
return pi0, q0
|
|
|
|
def act(ob, *args, **kwargs):
|
|
return sess.run(a, {X: ob})
|
|
|
|
self.step = step
|
|
self.out = out
|
|
self.act = act
|
|
|
|
class AcerLstmPolicy(object):
|
|
|
|
def __init__(self, sess, ob_space, ac_space, nenv, nsteps, nstack, reuse=False, nlstm=256):
|
|
nbatch = nenv * nsteps
|
|
nh, nw, nc = ob_space.shape
|
|
ob_shape = (nbatch, nh, nw, nc * nstack)
|
|
nact = ac_space.n
|
|
X = tf.placeholder(tf.uint8, ob_shape) # obs
|
|
M = tf.placeholder(tf.float32, [nbatch]) #mask (done t-1)
|
|
S = tf.placeholder(tf.float32, [nenv, nlstm*2]) #states
|
|
with tf.variable_scope("model", reuse=reuse):
|
|
h = nature_cnn(X)
|
|
|
|
# lstm
|
|
xs = batch_to_seq(h, nenv, nsteps)
|
|
ms = batch_to_seq(M, nenv, nsteps)
|
|
h5, snew = lstm(xs, ms, S, 'lstm1', nh=nlstm)
|
|
h5 = seq_to_batch(h5)
|
|
|
|
pi_logits = fc(h5, 'pi', nact, init_scale=0.01)
|
|
pi = tf.nn.softmax(pi_logits)
|
|
q = fc(h5, 'q', nact)
|
|
|
|
a = sample(pi_logits) # could change this to use self.pi instead
|
|
self.initial_state = np.zeros((nenv, nlstm*2), dtype=np.float32)
|
|
self.X = X
|
|
self.M = M
|
|
self.S = S
|
|
self.pi = pi # actual policy params now
|
|
self.q = q
|
|
|
|
def step(ob, state, mask, *args, **kwargs):
|
|
# returns actions, mus, states
|
|
a0, pi0, s = sess.run([a, pi, snew], {X: ob, S: state, M: mask})
|
|
return a0, pi0, s
|
|
|
|
self.step = step
|