Here are the examples of the python api numpy.random.randn.astype taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.
145 Examples
3
View Complete Implementation : simple_test.py
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
def test_send_to_node():
network = tn.ContainerNode("c", [
tn.SequentialNode(
"s1",
[tn.InputNode("in", shape=(3, 4, 5)),
tn.SendToNode("stn1", reference="s2")]),
tn.SequentialNode(
"s2",
[tn.SendToNode("stn2", reference="stn3")]),
tn.SequentialNode(
"s3",
[tn.SendToNode("stn3", reference="i")]),
tn.IdensatyNode("i"),
]).network()
fn = network.function(["in"], ["i"])
x = np.random.randn(3, 4, 5).astype(fX)
np.testing.astert_allclose(fn(x)[0], x)
3
View Complete Implementation : stochastic_test.py
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
def test_gaussian_dropout_node():
def make_network(p):
return tn.SequentialNode("s", [
tn.InputNode("i", shape=(3, 4, 5)),
tn.GaussianDropoutNode("do", p=p)
]).network()
x = np.random.randn(3, 4, 5).astype(fX)
fn1 = make_network(0).function(["i"], ["s"])
np.testing.astert_allclose(fn1(x)[0], x)
@nt.raises(astertionError)
def test_not_idensaty():
fn2 = make_network(0.5).function(["i"], ["s"])
np.testing.astert_allclose(fn2(x)[0], x)
test_not_idensaty()
3
View Complete Implementation : recurrent_convolution_test.py
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
def test_default_recurrent_conv_2d_node():
network = tn.SequentialNode(
"s",
[tn.InputNode("i", shape=(3, 4, 5, 6)),
rcl.DefaultRecurrentConv2DNode("a",
num_filters=7,
filter_size=(3, 3),
pad="same")]
).network()
fn = network.function(["i"], ["s"])
res = fn(np.random.randn(3, 4, 5, 6).astype(fX))[0]
np.testing.astert_equal((3, 7, 5, 6), res.shape)
3
View Complete Implementation : composite_test.py
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
def test_dense_combine_node():
network = tn.SequentialNode(
"seq",
[tn.InputNode("in", shape=(3, 4, 5)),
tn.DenseCombineNode("fc1", [tn.IdensatyNode("i1")], num_units=6),
tn.DenseCombineNode("fc2", [tn.IdensatyNode("i2")], num_units=7),
tn.DenseCombineNode("fc3", [tn.IdensatyNode("i3")], num_units=8)]
).network()
x = np.random.randn(3, 4, 5).astype(fX)
fn = network.function(["in"], ["fc3"])
res = fn(x)[0]
nt.astert_equal(res.shape, (3, 8))
3
View Complete Implementation : downsample_test.py
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
def test_custom_global_pool_node():
network = tn.SequentialNode(
"s",
[tn.InputNode("i", shape=(6, 5, 4, 3)),
tn.CustomGlobalPoolNode("gp", pool_function=T.mean)]
).network()
fn = network.function(["i"], ["s"])
x = np.random.randn(6, 5, 4, 3).astype(fX)
ans = x.mean(axis=(2, 3))
np.testing.astert_allclose(ans,
fn(x)[0],
rtol=1e-5,
atol=1e-7)
3
View Complete Implementation : theanode_test.py
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
def test_dimshuffle_node():
network = tn.SequentialNode(
"s",
[tn.InputNode("in", shape=(3, 4, 5)),
tn.DimshuffleNode("r", pattern=(1, "x", 0, 2))]
).network()
fn = network.function(["in"], ["s"])
x = np.random.randn(3, 4, 5).astype(fX)
ans = T.constant(x).dimshuffle(1, "x", 0, 2).eval()
res = fn(x)[0]
np.testing.astert_equal(res.shape, ans.shape)
np.testing.astert_equal(res, ans)
3
View Complete Implementation : downsample_test.py
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
def test_custom_global_pool_node():
network = tn.SequentialNode(
"s",
[tn.InputNode("i", shape=(6, 5, 4, 3)),
tn.CustomGlobalPoolNode("gp", pool_function=T.mean)]
).network()
fn = network.function(["i"], ["s"])
x = np.random.randn(6, 5, 4, 3).astype(fX)
ans = x.mean(axis=(2, 3))
np.testing.astert_allclose(ans,
fn(x)[0],
rtol=1e-5,
atol=1e-7)
3
View Complete Implementation : simple_test.py
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
def test_apply_node():
network = tn.SequentialNode("s", [
tn.InputNode("in", shape=(3, 4, 5)),
tn.ApplyNode("a", fn=T.sum, shape_fn=lambda x: ()),
]).network()
fn = network.function(["in"], ["s"])
x = np.random.randn(3, 4, 5).astype(fX)
np.testing.astert_allclose(fn(x)[0],
x.sum(),
rtol=1e-5)
3
View Complete Implementation : gradnet_test.py
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
def test_grad_net_interpolation_node():
network = tn.SequentialNode(
"s",
[tn.InputNode("i", shape=(1, 10)),
gradnet.GradNetInterpolationNode(
"gradnet",
{"early": tn.ReLUNode("r"),
"late": tn.TanhNode("t")},
late_gate=0.5)]
).network()
fn = network.function(["i"], ["s"])
x = np.random.randn(1, 10).astype(fX)
ans = 0.5 * np.clip(x, 0, np.inf) + 0.5 * np.tanh(x)
np.testing.astert_allclose(ans, fn(x)[0], rtol=1e-5)
3
View Complete Implementation : theanode_test.py
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
Copyright BSD 3-Clause "New" or "Revised" License
Author : SBU-BMI
def test_repeat_node():
network = tn.SequentialNode(
"s",
[tn.InputNode("in", shape=(3,)),
tn.RepeatNode("r", repeats=2, axis=0)]
).network()
fn = network.function(["in"], ["s"])
x = np.random.randn(3).astype(fX)
np.testing.astert_allclose(np.repeat(x, 2, 0),
fn(x)[0])