def test_infer_shape(self):
adscal = at.dscalar()
bdscal = at.dscalar()
adscal_val = np.random.random()
bdscal_val = np.random.random() + 1
out = assert_op(adscal, bdscal)
self._compile_and_check([adscal, bdscal], [out],
[adscal_val, bdscal_val], Assert)
admat = at.dmatrix()
admat_val = np.random.random((3, 4))
adscal_val += 1
out = assert_op(admat, adscal, bdscal)
self._compile_and_check([admat, adscal, bdscal], [out],
[admat_val, adscal_val, bdscal_val], Assert)
def test_CheckAndRaise_validation():
with pytest.raises(ValueError):
CheckAndRaise(str)
g1 = assert_op(np.array(1.0))
assert isinstance(g1.owner.inputs[0], Constant)
def test_one_assert_merge(self):
# Merge two nodes, one has assert, the other not.
x1 = matrix("x1")
x2 = matrix("x2")
e = dot(x1, x2) + dot(assert_op(x1, (x1 > x2).all()), x2)
g = FunctionGraph([x1, x2], [e], clone=False)
MergeOptimizer().optimize(g)
assert g.outputs[0].owner.op == add
add_inputs = g.outputs[0].owner.inputs
assert isinstance(add_inputs[0].owner.op, Dot)
# Confirm that the `Assert`s are correct
assert_var = add_inputs[0].owner.inputs[0]
assert_ref = assert_op(x1, (x1 > x2).all())
assert equal_computations([assert_var], [assert_ref])
# Confirm the merge
assert add_inputs[0] is add_inputs[1]
def test_both_assert_merge_identical(self):
"""Merge two nodes, both have `Assert`s on the same node with the same conditions."""
x1 = matrix("x1")
x2 = matrix("x2")
e = dot(assert_op(x1, (x1 > x2).all()), x2) + dot(
assert_op(x1, (x1 > x2).all()), x2)
g = FunctionGraph([x1, x2], [e], clone=False)
MergeOptimizer().optimize(g)
assert g.outputs[0].owner.op == add
add_inputs = g.outputs[0].owner.inputs
assert isinstance(add_inputs[0].owner.op, Dot)
# Confirm that the `Assert`s are correct
assert_var = add_inputs[0].owner.inputs[0]
assert_ref = assert_op(x1, (x1 > x2).all())
assert equal_computations([assert_var], [assert_ref])
# Confirm the merge
assert add_inputs[0] is add_inputs[1]
def test_jax_checkandraise():
p = scalar()
p.tag.test_value = 0
res = assert_op(p, p < 1.0)
res_fg = FunctionGraph([p], [res])
with pytest.raises(NotImplementedError):
compare_jax_and_py(res_fg, [1.0])
def test_both_assert_merge_2_reverse(self):
# Test case "test_both_assert_merge_2" but in reverse order
x1 = matrix("x1")
x2 = matrix("x2")
x3 = matrix("x3")
e = dot(x1, assert_op(x2, (x2 > x3).all())) + dot(
assert_op(x1, (x1 > x3).all()), x2)
g = FunctionGraph([x1, x2, x3], [e], clone=False)
MergeOptimizer().optimize(g)
assert g.outputs[0].owner.op == add
add_inputs = g.outputs[0].owner.inputs
assert isinstance(add_inputs[0].owner.op, Dot)
# Confirm that the `Assert`s are correct
assert_var_1, assert_var_2 = add_inputs[0].owner.inputs
assert_ref_1 = assert_op(x2, (x2 > x3).all())
assert equal_computations([assert_var_1], [assert_ref_1])
assert_ref_2 = assert_op(x1, (x1 > x3).all())
assert equal_computations([assert_var_2], [assert_ref_2])
# Confirm the merge
assert add_inputs[0] is add_inputs[1]
def test_CheckAndRaise_equal():
x, y = at.vectors("xy")
g1 = assert_op(x, (x > y).all())
g2 = assert_op(x, (x > y).all())
assert equal_computations([g1], [g2])
