def testEmpty(self):
x = np.random.rand(2, 2).astype(np.float32)
coeffs = []
np_val = np.polyval(coeffs, x)
with self.cached_session():
tf_val = math_ops.polyval(coeffs, x)
self.assertAllClose(np_val, self.evaluate(tf_val))
def _runtest(self, dtype, degree):
x = np.random.rand(2, 2).astype(dtype)
coeffs = [np.random.rand(2, 2).astype(dtype) for _ in range(degree + 1)]
np_val = np.polyval(coeffs, x)
with self.cached_session():
tf_val = math_ops.polyval(coeffs, x)
self.assertAllClose(np_val, self.evaluate(tf_val))
def f(p, x):
if p.shape.rank == 0:
p = array_ops.reshape(p, [1])
p = array_ops.unstack(p)
# TODO(wangpeng): Make tf version take a tensor for p instead of a list.
y = math_ops.polyval(p, x)
# If the polynomial is 0-order, numpy requires the result to be broadcast to
# `x`'s shape.
if len(p) == 1:
y = array_ops.broadcast_to(y, x.shape)
return y
def testBroadcast(self):
dtype = np.float32
degree = 3
shapes = [(1,), (2, 1), (1, 2), (2, 2)]
for x_shape in shapes:
for coeff_shape in shapes:
x = np.random.rand(*x_shape).astype(dtype)
coeffs = [
np.random.rand(*coeff_shape).astype(dtype)
for _ in range(degree + 1)
]
np_val = np.polyval(coeffs, x)
with self.cached_session():
tf_val = math_ops.polyval(coeffs, x)
self.assertAllClose(np_val, self.evaluate(tf_val))
def test_coeffs_raise(self):
x = np.random.rand(2, 2).astype(np.float32)
coeffs = {}
with self.assertRaisesRegexp(ValueError, "Argument coeffs must be list"):
math_ops.polyval(coeffs, x)
