import latplan
import latplan.puzzles.lightsout_twisted as p
import itertools
c = np.array([c for c in itertools.islice(p.generate_configs(4), 10000)])
from colors import color
from functools import partial
style = partial(color, fg='black', bg='white')
from latplan.util.timer import Timer
with Timer(
style(
"************************* states on cpu ***************************"
)):
s = p.generate_cpu(c)
with Timer(
style(
"************************* states on gpu, batch=100 ***************************"
)):
s = p.generate_gpu(c, batch_size=100)
with Timer(
style(
"************************* states on gpu, batch=1000 ***************************"
)):
s = p.generate_gpu(c, batch_size=1000)
importlib.reload(p)
p.setup()
import itertools
c = [ c for c in itertools.islice(p.generate_configs(9), 10000) ]
from colors import color
from functools import partial
style = partial(color, fg='black', bg='white')
from latplan.util.timer import Timer
with Timer(style("************************* states on gpu, batch=100 ***************************")):
s = p.generate(c,3,3, batch_size=100)
with Timer(style("************************* states on gpu, batch=1000 ***************************")):
s = p.generate(c,3,3, batch_size=1000)
with Timer(style("************************* validate_states on gpu, batch=100 ***************************")):
print("results:", np.all(p.validate_states(s,batch_size=100)), "(should be True)")
with Timer(style("************************* validate_states on gpu, batch=1000 ***************************")):
print("results:", np.all(p.validate_states(s,batch_size=1000)), "(should be True)")
with Timer(style("************************* validate_states + noise ***************************")):
results = p.validate_states(np.clip(s+np.random.normal(0,0.1,s.shape),0,1))
print("results:", np.all(results), "(should be True)")
aae.plot(transitions, "aae_all_actions_for_a_state.png", ae=ae)
from latplan.util.timer import Timer
# with Timer("loading csv..."):
# all_actions = np.loadtxt("{}/all_actions.csv".format(directory),dtype=np.int8)
# transitions = aae.decode([np.repeat(all_actions[:1,:N], len(all_labels), axis=0), all_labels])
suc = transitions[:,N:]
from latplan.util.plot import plot_grid, squarify
plot_grid([x for x in ae.decode_binary(suc)], w=8, path=aae.local("aae_all_actions_for_a_state_8x16.png"), verbose=True)
plot_grid([x for x in ae.decode_binary(suc)], w=16, path=aae.local("aae_all_actions_for_a_state_16x8.png"), verbose=True)
plot_grid(ae.decode_binary(data[:1,:N]), w=1, path=aae.local("aae_all_actions_for_a_state_state.png"), verbose=True)
if 'check' in mode:
from latplan.util.timer import Timer
with Timer("loading csv..."):
all_actions = np.loadtxt("{}/all_actions.csv".format(directory),dtype=np.int8)
with Timer("shuffling"):
random.shuffle(all_actions)
all_actions = all_actions[:10000]
count = 0
try:
pre_states = all_actions[:,:N]
suc_states = all_actions[:,N:]
pre_images = ae.decode_binary(pre_states,batch_size=1000)
suc_images = ae.decode_binary(suc_states,batch_size=1000)
import progressbar as pb
bar = pb.ProgressBar(