def test_gatedlayer_deltas_finite_differences(self):
t = 7
b = 5
check_errors = []
for act_func in ["sigmoid", "relu"]:
net = self.build_gatedlayer_network(3, act_func)
e, grad_calc, grad_approx = check_deltas(net, n_batches=b, n_timesteps=t, rnd=rnd)
check_errors.append(e)
if e > 1e-4:
diff = (grad_approx - grad_calc).reshape(t, b, -1)
for t in range(diff.shape[0]):
print("======== t=%d =========" % t)
print(diff[t])
# print("Checking Deltas of %s with %s = %0.4f" % (l(3), a, e))
self.assertTrue(np.all(np.array(check_errors) < 1e-4))
def test_deltas_finite_differences(self):
t = 7
b = 5
check_errors = []
for l, a in itertools.product(self.layer_types, self.activation_functions):
net = self.build_network(l, a)
e, grad_calc, grad_approx = check_deltas(net, n_batches=b,
n_timesteps=t, rnd=rnd)
check_errors.append(e)
if e > 1e-4:
diff = (grad_approx - grad_calc).reshape(t, b, -1)
for t in range(diff.shape[0]):
print("======== t=%d =========" % t)
print(diff[t])
print("Checking Deltas of %s with %s = %0.4f" % (l(3), a, e))
self.assertTrue(np.all(np.array(check_errors) < 1e-4))
def test_deltas_finite_differences(self):
t = 7
b = 5
check_errors = []
for cfg in self.lstm_configs:
net = self.build_network(cfg)
e, grad_calc, grad_approx = check_deltas(net, n_batches=b,
n_timesteps=t, rnd=rnd)
check_errors.append(e)
if e > 1e-6:
diff = (grad_approx - grad_calc).reshape(t, b, -1)
for t in range(diff.shape[0]):
print("======== t=%d =========" % t)
print(diff[t])
print("Checking Deltas of Lstm97 with %s = %0.6f" % (cfg, e))
self.assertTrue(np.all(np.array(check_errors) < 1e-6))
def test_deltas_finite_differences(self):
e, grad_calc, grad_approx = check_deltas(self.net, n_batches=self.batch_size,
n_timesteps=self.timesteps, rnd=rnd)
grad_approx = grad_approx.reshape(self.timesteps, self.batch_size, -1)
grad_calc = grad_calc.reshape(self.timesteps, self.batch_size, -1)
diff = (grad_approx - grad_calc)
for t in range(diff.shape[0]):
print("======== t=%d =========" % t)
print("calc")
print(grad_calc[t])
print("approx")
print(grad_approx[t])
print("diff")
print(diff[t])
print(np.sum(diff[t]**2))
print("Checking Deltas of ClockworkLayer with sigmoid = %0.4f" % e)
self.assertTrue(e < 1e-6)
def test_staticlstm_deltas_finite_differences(self):
t = 7
b = 5
check_errors = []
net = self.build_staticlstm_network(3, 'sigmoid')
e, grad_calc, grad_approx = check_deltas(net,
n_batches=b,
n_timesteps=t,
rnd=rnd)
check_errors.append(e)
if e > 1e-4:
diff = (grad_approx - grad_calc).reshape(t, b, -1)
for t in range(diff.shape[0]):
print("======== t=%d =========" % t)
print(diff[t])
# print("Checking Deltas of %s with %s = %0.4f" % (l(3), a, e))
self.assertTrue(np.all(np.array(check_errors) < 1e-4))
def test_deltas_finite_differences(self):
e, grad_calc, grad_approx = check_deltas(self.net,
n_batches=self.batch_size,
n_timesteps=self.timesteps,
rnd=rnd)
grad_approx = grad_approx.reshape(self.timesteps, self.batch_size, -1)
grad_calc = grad_calc.reshape(self.timesteps, self.batch_size, -1)
diff = (grad_approx - grad_calc)
for t in range(diff.shape[0]):
print("======== t=%d =========" % t)
print("calc")
print(grad_calc[t])
print("approx")
print(grad_approx[t])
print("diff")
print(diff[t])
print(np.sum(diff[t]**2))
print("Checking Deltas of ClockworkLayer with sigmoid = %0.4f" % e)
self.assertTrue(e < 1e-6)
def test_deltas_finite_differences(self):
t = 7
b = 5
check_errors = []
for l, a in itertools.product(self.layer_types,
self.activation_functions):
net = self.build_network(l, a)
e, grad_calc, grad_approx = check_deltas(net,
n_batches=b,
n_timesteps=t,
rnd=rnd)
check_errors.append(e)
if e > 1e-4:
diff = (grad_approx - grad_calc).reshape(t, b, -1)
for t in range(diff.shape[0]):
print("======== t=%d =========" % t)
print(diff[t])
print("Checking Deltas of %s with %s = %0.4f" % (l(3), a, e))
self.assertTrue(np.all(np.array(check_errors) < 1e-4))
