def test_save_and_load_params():
params = Dense(2).init_parameters(np.zeros((1, 2)), key=PRNGKey(0))
from pathlib import Path
path = Path('/') / 'tmp' / 'net.params'
save(params, path)
params_ = load(path)
assert_dense_parameters_equal(params, params_)
def test_submodule_reuse_top_level():
net = Dense(2)
inputs = np.zeros((1, 3))
params = net.init_parameters(inputs, key=PRNGKey(0))
out = net.apply(params, inputs)
params_ = net.init_parameters(inputs, key=PRNGKey(1), reuse={net: params})
assert_dense_parameters_equal(params, params_)
out_ = net.apply(params_, inputs)
assert np.array_equal(out, out_)
def test_submodule_reuse():
inputs = np.zeros((1, 2))
layer = Dense(5)
net1 = Sequential(layer, Dense(2))
net2 = Sequential(layer, Dense(3))
layer_params = layer.init_parameters(inputs, key=PRNGKey(0))
net1_params = net1.init_parameters(inputs,
key=PRNGKey(1),
reuse={layer: layer_params})
net2_params = net2.init_parameters(inputs,
key=PRNGKey(2),
reuse={layer: layer_params})
out1 = net1.apply(net1_params, inputs)
assert out1.shape == (1, 2)
out2 = net2.apply(net2_params, inputs)
assert out2.shape == (1, 3)
assert_dense_parameters_equal(layer_params, net1_params[0])
assert_dense_parameters_equal(layer_params, net2_params[0])
new_layer_params = layer.init_parameters(inputs, key=PRNGKey(3))
combined_params = net1.parameters_from(
{
net1: net1_params,
layer: new_layer_params
}, inputs)
assert_dense_parameters_equal(new_layer_params, combined_params.dense0)
assert_dense_parameters_equal(net1_params.dense1, combined_params.dense1)
def test_parameters_from_top_level():
net = Dense(2)
inputs = np.zeros((1, 3))
params = net.init_parameters(inputs, key=PRNGKey(0))
out = net.apply(params, inputs)
params_ = net.parameters_from({net: params}, inputs)
assert_dense_parameters_equal(params, params_)
out_ = net.apply(params_, inputs)
assert np.array_equal(out, out_)
out_ = net.apply_from({net: params}, inputs)
assert np.array_equal(out, out_)
out_ = net.apply_from({net: params}, inputs, jit=True)
assert np.array_equal(out, out_)
def test_parameters_from_sharing_between_multiple_parents():
a = Dense(2)
b = Sequential(a, np.sum)
@parametrized
def net(inputs):
return a(inputs), b(inputs)
inputs = np.zeros((1, 3))
a_params = a.init_parameters(inputs, key=PRNGKey(0))
out = a.apply(a_params, inputs)
params = net.parameters_from({a: a_params}, inputs)
assert_dense_parameters_equal(a_params, params.dense)
assert_parameters_equal((), params.sequential)
assert 2 == len(params)
out_, _ = net.apply(params, inputs)
assert np.array_equal(out, out_)
def test_submodule_reuse():
inputs = np.zeros((1, 2))
layer = Dense(5)
net1 = Sequential(layer, Dense(2))
net2 = Sequential(layer, Dense(3))
layer_params = layer.init_parameters(PRNGKey(0), inputs)
net1_params = net1.init_parameters(PRNGKey(1), inputs, reuse={layer: layer_params})
net2_params = net2.init_parameters(PRNGKey(2), inputs, reuse={layer: layer_params})
out1 = net1.apply(net1_params, inputs)
assert out1.shape == (1, 2)
out2 = net2.apply(net2_params, inputs)
assert out2.shape == (1, 3)
assert_dense_parameters_equal(layer_params, net1_params[0])
assert_dense_parameters_equal(layer_params, net2_params[0])
def test_parameters_from_subsubmodule():
subsublayer = Dense(2)
sublayer = Sequential(subsublayer, relu)
net = Sequential(sublayer, np.sum)
inputs = np.zeros((1, 3))
params = net.init_parameters(inputs, key=PRNGKey(0))
out = net.apply(params, inputs)
subsublayer_params = subsublayer.init_parameters(inputs, key=PRNGKey(0))
params_ = net.parameters_from({subsublayer: subsublayer_params}, inputs)
assert_dense_parameters_equal(subsublayer_params, params_[0][0])
out_ = net.apply(params_, inputs)
assert out.shape == out_.shape
out_ = net.apply_from({subsublayer: subsublayer_params}, inputs)
assert out.shape == out_.shape
out_ = net.apply_from({subsublayer: subsublayer_params}, inputs, jit=True)
assert out.shape == out_.shape
def test_parameters_from_diamond_shared_submodules():
sublayer = Dense(2)
a = Sequential(sublayer, relu)
b = Sequential(sublayer, np.sum)
@parametrized
def net(inputs):
return a(inputs), b(inputs)
inputs = np.zeros((1, 3))
a_params = a.init_parameters(PRNGKey(0), inputs)
out = a.apply(a_params, inputs)
params = net.parameters_from({a: a_params}, inputs)
assert_dense_parameters_equal(a_params.dense, params.sequential0.dense)
assert_dense_parameters_equal(a_params.dense, params.sequential1.dense)
# TODO parameters are duplicated, optimization with weight sharing is wrong:
# TODO assert 1 == len(params)
out_, _ = net.apply(params, inputs)
assert np.array_equal(out, out_)
