Datasets:
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import time
import elements
import zerofun
import numpy as np
class TestAgent:
def __init__(self, obs_space, act_space, addr=None):
self.obs_space = obs_space
self.act_space = act_space
if addr:
self.client = zerofun.Client(addr, connect=True)
self.should_stats = elements.when.Clock(1)
else:
self.client = None
self._stats = {
'env_steps': 0, 'replay_steps': 0, 'reports': 0,
'saves': 0, 'loads': 0, 'created': time.time(),
}
def _watcher(self):
while True:
if self.queue.empty():
self.queue.put(self.stats())
else:
time.sleep(0.01)
def stats(self):
stats = self._stats.copy()
stats['lifetime'] = time.time() - stats.pop('created')
return stats
def init_policy(self, batch_size):
return (np.zeros(batch_size),)
def init_train(self, batch_size):
return (np.zeros(batch_size),)
def init_report(self, batch_size):
return ()
def policy(self, carry, obs, mode='train'):
assert set(obs.keys()) == set(self.obs_space.keys())
B = len(obs['is_first'])
self._stats['env_steps'] += B
carry, = carry
carry = np.asarray(carry)
assert carry.shape == (B,)
assert not any(k.startswith('log/') for k in obs.keys())
target = (carry + 1) * (1 - obs['is_first'])
assert (obs['count'] == target).all()
carry = target
if self.client and self.should_stats():
self.client.report(self.stats())
act = {
k: np.stack([v.sample() for _ in range(B)])
for k, v in self.act_space.items() if k != 'reset'}
return (carry,), act, {}
def train(self, carry, data):
expected = sorted(set(self.obs_space | self.act_space) | {'stepid'})
assert sorted(data.keys()) == expected, (sorted(data.keys()), expected)
B, T = data['count'].shape
carry, = carry
assert carry.shape == (B,)
assert not any(k.startswith('log/') for k in data.keys())
self._stats['replay_steps'] += B * T
for t in range(T):
current = data['count'][:, t]
reset = data['is_first'][:, t]
target = (1 - reset) * (carry + 1) + reset * current
assert (current == target).all()
carry = current
outs = {}
metrics = {}
return (carry,), outs, metrics
def report(self, carry, data):
self._stats['reports'] += 1
return carry, {
'scalar': np.float32(0),
'vector': np.zeros(10),
'image1': np.zeros((64, 64, 1)),
'image3': np.zeros((64, 64, 3)),
'video': np.zeros((10, 64, 64, 3)),
}
def dataset(self, generator):
return generator()
def save(self):
self._stats['saves'] += 1
return self._stats
def load(self, data):
self._stats = data
self._stats['loads'] += 1
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