class serv_ESN:
def __init__(self,):
weight_scale = 1.0 # .8
weight_inp = 0.2
weight_fb = 10 ** (-3)
alpha = 0.99 # .35#.2
fback = False # False
inital_washout = 100 # 100
padding_s = 300
units = 28 * 28
indim = 6
outdim = 6
self.esn = ESN(units, indim, outdim, weight_scale, weight_inp, weight_fb, alpha, fback)
# self.webapp = webapp
local_dir = os.path.dirname(__file__)
self.esn.load(local_dir + "/trainied.pickle")
self.stepper = self.esn.step_taped()
self.outputs = np.zeros((3, outdim))
print "ESN:: init"
def serv_close(self,):
return True
def serv_train(self,):
return True
def serv_step(self, val_in):
state, output, this = self.stepper(val_in, self.outputs, 0.0)
output += np.random.random(output.shape)
return state, output
def test(sys, weight_scale, weight_inp, weight_fb, alpha, inital_washout, padding_s ):
units = 28*28
indim = 6
outdim = 6
esn = ESN(
units, indim, outdim, weight_scale,weight_inp,weight_fb, alpha, fback
)
esn.load("trainied.pickle")
stepper = esn.step_taped()
dtsets = read_dataset(sys.argv[1], sys.argv[2])
# import pdb;pdb.set_trace()
inputs, outputs, padIdxs, idxs = dtsets[0]
plot_output =[]
plot_state =[]
import time
start = time.time()
###########TRAIN
# all_states = []
# all_this = []
# all_states, all_this= train(idxs, padIdxs, esn, stepper, inputs, outputs)
# M_tonos = np.linalg.pinv(all_states)
# # import pdb; pdb.set_trace()
# all_this = np.arctanh(all_this)
# W_trans = np.dot(M_tonos,all_this)
# esn.W_out.set_value(W_trans)
# print W_trans
###########END TRAIN
print "Time taken ", time.time() - start
#########TESTING#############
outputs1 = np.zeros(outputs.shape)
outputs1[1:] = outputs[:-1]
state, output, this = stepper(
inputs, outputs, 0.)
print output.shape
plot_state.extend(state[:,:units])
plot_output.extend(output)
#########TESTING#############
if int(sys.argv[3]) == 1:
f, axarr = plt.subplots(4, sharex=True)
for oid,tpt in enumerate(np.array(plot_output).transpose()):
try:
axarr[0].plot(tpt,label="output"+str(oid))
except:
pass
axarr[0].set_title('output')
# axarr[0].legend()
axarr[1].plot(outputs,label="outputs")
axarr[2].plot(plot_state,label="state")
axarr[2].set_title('state')
# axarr[1].legend()
axarr[3].plot(inputs,label="inputs")
axarr[3].set_title('inputs')
# axarr[2].legend()
# plt.draw()
# plt.figure()
# plt.plot(inputs)
# # plt.figure()
# plt.plot(outputs)
plt.show()
