def test_insert_inplace(self):
mySymbolicMatricesList = TypedListType(
tt.TensorType(theano.config.floatX, (False, False)))()
mySymbolicIndex = tt.scalar(dtype="int64")
mySymbolicMatrix = tt.matrix()
z = Insert()(mySymbolicMatricesList, mySymbolicIndex, mySymbolicMatrix)
m = theano.compile.mode.get_default_mode().including(
"typed_list_inplace_opt")
f = theano.function(
[
In(mySymbolicMatricesList, borrow=True, mutable=True),
mySymbolicIndex,
mySymbolicMatrix,
],
z,
accept_inplace=True,
mode=m,
)
assert f.maker.fgraph.toposort()[0].op.inplace
x = rand_ranged(-1000, 1000, [100, 101])
y = rand_ranged(-1000, 1000, [100, 101])
assert np.array_equal(f([x], np.asarray(1, dtype="int64"), y), [x, y])
def test_sanity_check(self):
mySymbolicMatricesList = TypedListType(
T.TensorType(theano.config.floatX, (False, False)))()
myMatrix = T.matrix()
myScalar = T.scalar()
z = Insert()(mySymbolicMatricesList, myScalar, myMatrix)
f = theano.function([mySymbolicMatricesList, myScalar, myMatrix], z)
x = rand_ranged_matrix(-1000, 1000, [100, 101])
y = rand_ranged_matrix(-1000, 1000, [100, 101])
self.assertTrue(numpy.array_equal(f([x], numpy.asarray(1), y), [x, y]))
def test_sanity_check(self):
mySymbolicMatricesList = TypedListType(
tt.TensorType(theano.config.floatX, (False, False))
)()
myMatrix = tt.matrix()
myScalar = tt.scalar(dtype="int64")
z = Insert()(mySymbolicMatricesList, myScalar, myMatrix)
f = theano.function([mySymbolicMatricesList, myScalar, myMatrix], z)
x = rand_ranged_matrix(-1000, 1000, [100, 101])
y = rand_ranged_matrix(-1000, 1000, [100, 101])
assert np.array_equal(f([x], np.asarray(1, dtype="int64"), y), [x, y])
def test_inplace(self):
mySymbolicMatricesList = TypedListType(
T.TensorType(theano.config.floatX, (False, False)))()
myMatrix = T.matrix()
myScalar = T.scalar(dtype="int64")
z = Insert(True)(mySymbolicMatricesList, myScalar, myMatrix)
f = theano.function([mySymbolicMatricesList, myScalar, myMatrix],
z,
accept_inplace=True)
x = rand_ranged_matrix(-1000, 1000, [100, 101])
y = rand_ranged_matrix(-1000, 1000, [100, 101])
assert np.array_equal(f([x], np.asarray(1, dtype="int64"), y), [x, y])
