def testLeakyRelu(self): values = (numpy.array([-100., -10., 1., 0, 1., 10., 100.], dtype=numpy.float32)) tensor = tf.constant(values) out = self.Run(functions.leaky_relu(tensor)) for i in range(len(values)): values[i] *= 0.01 if values[i] < 0 else 1 testing.assert_allclose(out[0], values, rtol=TOLERANCE)
def test_leaky_relu(self): values = (numpy.array([-100., -10., 1., 0, 1., 10., 100.], dtype=numpy.float32)) tensor = tf.constant(values) out = self.eval_tensor(functions.leaky_relu(tensor)) for i, value in enumerate(values): if value < 0: values[i] *= 0.01 testing.assert_allclose(out[0], values, rtol=TOLERANCE, atol=TOLERANCE)
def testLeakyRelu(self): values = ( numpy.array( [-100., -10., 1., 0, 1., 10., 100.], dtype=numpy.float32)) tensor = tf.constant(values) out = self.Run(functions.leaky_relu(tensor)) for i in range(len(values)): values[i] *= 0.01 if values[i] < 0 else 1 testing.assert_allclose(out[0], values, rtol=TOLERANCE)
def test_leaky_relu(self): values = ( numpy.array( [-100., -10., 1., 0, 1., 10., 100.], dtype=numpy.float32)) tensor = tf.constant(values) out = self.eval_tensor(functions.leaky_relu(tensor)) for i, value in enumerate(values): if value < 0: values[i] *= 0.01 testing.assert_allclose(out[0], values, rtol=TOLERANCE, atol=TOLERANCE)