def test_tanh_cc2tensor():
tntest = Tanh()
from neon.backends.cc2 import GPU, GPUTensor
inputs = np.array([0, 1, -2]).reshape((3, 1))
outputs = GPUTensor([true_tanh(0), true_tanh(1), true_tanh(-2)])
be = GPU(rng_seed=0)
temp = be.zeros((3, 1))
tntest.apply_function(be, GPUTensor(inputs), temp)
assert_tensor_near_equal(outputs, temp)
def test_tanh_cputensor():
tntest = Tanh()
be = CPU(rng_seed=0)
CPUTensor([0, 1, -2])
inputs = np.array([0, 1, -2])
temp = be.zeros(inputs.shape)
outputs = np.array([true_tanh(0), true_tanh(1), true_tanh(-2)])
tntest.apply_function(be, CPUTensor(inputs), temp)
assert_tensor_near_equal(CPUTensor(outputs), temp)
def test_tanh_derivative_cputensor():
tntest = Tanh()
inputs = np.array([0, 1, -2])
be = CPU(rng_seed=0)
outputs = np.array(
[1 - true_tanh(0)**2, 1 - true_tanh(1)**2, 1 - true_tanh(-2)**2])
temp = be.zeros(inputs.shape)
tntest.apply_derivative(be, CPUTensor(inputs), temp)
assert_tensor_near_equal(CPUTensor(outputs), temp)
def test_tanh_cc2tensor():
tntest = Tanh()
from neon.backends.cc2 import GPU, GPUTensor
inputs = np.array([0, 1, -2]).reshape((3, 1))
outputs = GPUTensor([true_tanh(0), true_tanh(1), true_tanh(-2)])
be = GPU(rng_seed=0)
temp = be.zeros((3, 1))
tntest.apply_function(be, GPUTensor(inputs), temp)
assert_tensor_near_equal(outputs, temp)
def test_tanh_cputensor():
tntest = Tanh()
be = CPU(rng_seed=0)
CPUTensor([0, 1, -2])
inputs = np.array([0, 1, -2])
temp = be.zeros(inputs.shape)
outputs = np.array([true_tanh(0), true_tanh(1), true_tanh(-2)])
tntest.apply_function(be, CPUTensor(inputs), temp)
assert_tensor_near_equal(CPUTensor(outputs), temp)
def test_tanh_derivative_cputensor():
tntest = Tanh()
inputs = np.array([0, 1, -2])
be = CPU(rng_seed=0)
outputs = np.array([1 - true_tanh(0) ** 2,
1 - true_tanh(1) ** 2,
1 - true_tanh(-2) ** 2])
temp = be.zeros(inputs.shape)
tntest.apply_derivative(be, CPUTensor(inputs), temp)
assert_tensor_near_equal(CPUTensor(outputs), temp)
def test_tanh_derivative_cc2tensor():
tntest = Tanh()
from neon.backends.cc2 import GPU, GPUTensor
inputs = np.array([0, 1, -2], dtype='float32').reshape((3, 1))
be = GPU(rng_seed=0)
outputs = GPUTensor(
[1 - true_tanh(0)**2, 1 - true_tanh(1)**2, 1 - true_tanh(-2)**2])
temp = be.zeros(inputs.shape)
tntest.apply_derivative(be, GPUTensor(inputs, dtype='float32'), temp)
assert_tensor_near_equal(outputs, temp, tolerance=1e-5)
def test_tanh_derivative_cc2tensor():
tntest = Tanh()
from neon.backends.cc2 import GPU, GPUTensor
inputs = np.array([0, 1, -2], dtype='float32').reshape((3, 1))
be = GPU(rng_seed=0)
outputs = GPUTensor([1 - true_tanh(0) ** 2,
1 - true_tanh(1) ** 2,
1 - true_tanh(-2) ** 2])
temp = be.zeros(inputs.shape)
tntest.apply_derivative(be, GPUTensor(inputs, dtype='float32'), temp)
assert_tensor_near_equal(outputs, temp, tolerance=1e-5)
