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_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)