def test_predict(input_units, hidden_units, nr_samples, rgen):
nn = FcClassifier(input_units, hidden_units)
nn.init_random()
parameters = nn.get_weights()
weights = list(rgen.randn(*w.shape) for w, _ in parameters)
biases = list(np.zeros(b.shape) for _, b in parameters)
for n, (w, b) in enumerate(zip(weights, biases)):
nn.set_weights(n, w, b)
x_in = rgen.randn(input_units, nr_samples)
y_ref = fcnn_predict(x_in, weights, biases, it.repeat(sigmoid))[0, :]
y_hat = nn.predict(x_in)
assert_almost_equal(y_hat, y_ref)
def test_view_set_weights():
shape = (5, 8, 1)
nn = FcClassifier(shape[0], shape[1:-1])
weights = nn.get_weights()
for i in range(len(shape) - 1):
# +1 Due to implicit weights
w, b = weights[i]
assert w.shape == (shape[i + 1], shape[i])
assert b.shape == (shape[i + 1], )
new_weight = np.random.randn(shape[1], shape[0])
new_bias = np.random.randn(shape[1], )
nn.set_weights(0, new_weight, new_bias)
assert_array_equal(new_weight, nn.get_weights()[0][0])
assert_array_equal(new_bias, nn.get_weights()[0][1])
def test_set_weights_exception(rgen):
shape = (5, 1)
nn = FcClassifier(shape[0], tuple())
try:
nn.set_weights(0, rgen.randn(shape[1] + 3, shape[0]),
rgen.randn(shape[1]))
except ValueError:
pass
else:
raise AssertionError(
"Setting weight with wrong shape should raise error")
try:
nn.set_weights(0, rgen.randn(shape[1], shape[0]),
rgen.randn(shape[1] + 1))
except ValueError:
pass
else:
raise AssertionError(
"Setting bias with wrong shape should raise error")
def test_view_set_weights_permissions():
shape = (5, 1)
nn = FcClassifier(shape[0], tuple())
new_weight = np.random.randn(shape[1], shape[0])
new_bias = np.random.randn(shape[1], )
new_weight_copy = new_weight.copy()
new_bias_copy = new_bias.copy()
nn.set_weights(0, new_weight, new_bias)
new_weight[:] = 0
new_bias[:] = 0
nn_weight, nn_bias = nn.get_weights()[0]
assert_array_equal(new_weight_copy, nn_weight)
assert_array_equal(new_bias_copy, nn_bias)
assert not nn_weight.flags['OWNDATA']
assert not nn_bias.flags['OWNDATA']
assert not nn_weight.flags['WRITEABLE']
assert not nn_bias.flags['WRITEABLE']
del nn
assert_array_equal(new_weight_copy, nn_weight)
assert_array_equal(new_bias_copy, nn_bias)