def test_multidimensional_product(self, t1, t2):
"""Test that the multi-dimensional dot product reduces across the last dimension of the first
tensor, and the second-to-last dimension of the second tensor."""
res = fn.dot(t1, t2)
expected = np.array([[[[7, 7], [9, 5]], [[15, 15], [21, 11]],
[[2, 2], [0, 1]]],
[[[23, 23], [33, 17]], [[-3, -3], [-3, -2]],
[[5, 5], [9, 4]]]])
assert fn.allequal(res, expected)
def test_allequal(t1, t2):
"""Test that the allequal function works for a variety of inputs."""
res = fn.allequal(t1, t2)
if isinstance(t1, tf.Variable):
t1 = tf.convert_to_tensor(t1)
if isinstance(t2, tf.Variable):
t2 = tf.convert_to_tensor(t2)
expected = all(float(x) == float(y) for x, y in zip(t1, t2))
assert res == expected
def test_cast_like(t1, t2):
"""Test that casting t1 like t2 results in t1 being cast to the same datatype as t2"""
res = fn.cast_like(t1, t2)
# if tensorflow or pytorch, extract view of underlying data
if hasattr(res, "numpy"):
res = res.numpy()
if hasattr(t2, "numpy"):
t2 = t2.numpy()
assert fn.allequal(res, t1)
assert onp.asarray(res).dtype.type is onp.asarray(t2).dtype.type
def test_convert_tensor_like(self, t1, t2):
"""Test that converting t1 like t2 results in t1 being cast to the same tensor type as t2"""
res = fn.convert_like(t1, t2)
# if tensorflow or pytorch, extract view of underlying data
if hasattr(res, "numpy"):
res = res.numpy()
if hasattr(t2, "numpy"):
t2 = t2.numpy()
assert fn.allequal(res, t1)
assert isinstance(res, np.ndarray if isinstance(t2, (list, tuple)) else t2.__class__)
def test_toarray(t):
"""Test that the toarray method correctly converts the input
tensor into a NumPy array."""
res = fn.toarray(t)
assert fn.allequal(res, t)
assert isinstance(res, onp.ndarray)
def test_matrix_matrix_product(self, t1, t2):
"""Test that the matrix-matrix dot product of two vectors results in a matrix"""
res = fn.dot(t1, t1)
assert fn.allequal(res, np.array([[7, 10], [15, 22]]))
def test_vector_matrix_product(self, t1, t2):
"""Test that the vector-matrix dot product of two vectors results in a vector"""
res = fn.dot(t2, t1)
assert fn.allequal(res, [27, 40])
def test_matrix_vector_product(self, t1, t2):
"""Test that the matrix-vector dot product of two vectors results in a vector"""
res = fn.dot(t1, t2)
assert fn.allequal(res, [20, 46])
def test_vector_product(self, t1, t2):
"""Test that the dot product of two vectors results in a scalar"""
res = fn.dot(t1, t2)
assert fn.allequal(res, 14)
def test_convert_scalar(self, t_like):
"""Test that a python scalar is converted to a scalar tensor"""
res = fn.convert_like(5, t_like)
assert isinstance(res, t_like.__class__)
assert res.ndim == 0
assert fn.allequal(res, [5])
def test_arcsin(t):
"""Test that the arcsin function works for a variety
of input"""
res = fn.arcsin(t)
assert fn.allequal(res, np.arcsin([1, 0.2, -0.5]))
def test_angle(t):
"""Test that the angle function works for a variety
of input"""
res = fn.angle(t)
assert fn.allequal(res, [0, np.pi / 2, np.pi / 4])
def test_abs(t):
"""Test that the absolute function works for a variety
of input"""
res = fn.abs_(t)
assert fn.allequal(res, [1, 2, 5])
def test_conj(t):
res = fn.conj(t)
assert fn.allequal(res, np.conj(t))
