def test_inplace(self):
mySymbolicMatricesList = TypedListType(
T.TensorType(theano.config.floatX, (False, False)))()
myMatrix = T.matrix()
z = Append(True)(mySymbolicMatricesList, myMatrix)
f = theano.function([mySymbolicMatricesList, myMatrix],
z,
accept_inplace=True)
x = rand_ranged_matrix(-1000, 1000, [100, 101])
y = rand_ranged_matrix(-1000, 1000, [100, 101])
self.assertTrue(numpy.array_equal(f([x], y), [x, y]))
def test_sanity_check(self):
mySymbolicMatricesList = TypedListType(T.TensorType(
theano.config.floatX, (False, False)))()
myMatrix = T.matrix()
myScalar = T.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])
self.assertTrue(numpy.array_equal(f([x], numpy.asarray(1,
dtype='int64'), y), [x, y]))
def test_sanity_check_single(self):
mySymbolicMatricesList = TypedListType(
T.TensorType(theano.config.floatX, (False, False)))()
mySymbolicScalar = T.scalar(dtype='int64')
z = GetItem()(mySymbolicMatricesList, mySymbolicScalar)
f = theano.function([mySymbolicMatricesList, mySymbolicScalar], 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(0, dtype='int64')), x))
def test_sanity_check_slice(self):
mySymbolicMatricesList = TypedListType(
T.TensorType(theano.config.floatX, (False, False)))()
mySymbolicSlice = SliceType()()
z = GetItem()(mySymbolicMatricesList, mySymbolicSlice)
self.assertFalse(isinstance(z, T.TensorVariable))
f = theano.function([mySymbolicMatricesList, mySymbolicSlice], z)
x = rand_ranged_matrix(-1000, 1000, [100, 101])
self.assertTrue(numpy.array_equal(f([x], slice(0, 1, 1)), [x]))
def test_comparison_uneven_nested(self):
# test for comparison between uneven nested list
myType = TypedListType(T.TensorType(theano.config.floatX, (False, False)))
myManualNestedType1 = TypedListType(TypedListType(TypedListType(myType)))
myManualNestedType2 = TypedListType(TypedListType(myType))
assert myManualNestedType1 != myManualNestedType2
assert myManualNestedType2 != myManualNestedType1
def test_constant_input(self):
mySymbolicMatricesList = TypedListType(
T.TensorType(theano.config.floatX, (False, False)))()
z = GetItem()(mySymbolicMatricesList, 0)
f = theano.function([mySymbolicMatricesList], z)
x = rand_ranged_matrix(-1000, 1000, [100, 101])
self.assertTrue(numpy.array_equal(f([x]), x))
z = GetItem()(mySymbolicMatricesList, slice(0, 1, 1))
f = theano.function([mySymbolicMatricesList], z)
self.assertTrue(numpy.array_equal(f([x]), [x]))
def test_append_inplace(self):
mySymbolicMatricesList = TypedListType(T.TensorType(
theano.config.floatX, (False, False)))()
mySymbolicMatrix = T.matrix()
z = Append()(mySymbolicMatricesList, mySymbolicMatrix)
m = theano.compile.mode.get_default_mode().including("typed_list_inplace_opt")
f = theano.function([In(mySymbolicMatricesList, borrow=True,
mutable=True),
In(mySymbolicMatrix, borrow=True,
mutable=True)], z, accept_inplace=True, mode=m)
self.assertTrue(f.maker.fgraph.toposort()[0].op.inplace)
x = rand_ranged_matrix(-1000, 1000, [100, 101])
y = rand_ranged_matrix(-1000, 1000, [100, 101])
self.assertTrue(numpy.array_equal(f([x], 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])
def test_interface(self):
mySymbolicMatricesList = TypedListType(
T.TensorType(theano.config.floatX, (False, False)))()
mySymbolicScalar = T.scalar()
z = mySymbolicMatricesList[mySymbolicScalar]
f = theano.function([mySymbolicMatricesList, mySymbolicScalar], z)
x = rand_ranged_matrix(-1000, 1000, [100, 101])
self.assertTrue(numpy.array_equal(f([x], numpy.asarray(0)), x))
z = mySymbolicMatricesList[0:1:1]
f = theano.function([mySymbolicMatricesList], z)
self.assertTrue(numpy.array_equal(f([x]), [x]))
def test_interface(self):
mySymbolicMatricesList = TypedListType(
T.TensorType(theano.config.floatX, (False, False)))()
mySymbolicScalar = T.scalar(dtype="int64")
z = mySymbolicMatricesList[mySymbolicScalar]
f = theano.function([mySymbolicMatricesList, mySymbolicScalar], z)
x = rand_ranged_matrix(-1000, 1000, [100, 101])
assert np.array_equal(f([x], np.asarray(0, dtype="int64")), x)
z = mySymbolicMatricesList[0]
f = theano.function([mySymbolicMatricesList], z)
assert np.array_equal(f([x]), x)
def test_reverse_inplace(self):
mySymbolicMatricesList = TypedListType(
tt.TensorType(theano.config.floatX, (False, False)))()
z = Reverse()(mySymbolicMatricesList)
m = theano.compile.mode.get_default_mode().including(
"typed_list_inplace_opt")
f = theano.function(
[In(mySymbolicMatricesList, borrow=True, mutable=True)],
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, y]), [y, x])
def test_comparison_uneven_nested(self):
"""
test for comparison between uneven nested list
"""
myType = TypedListType(T.TensorType(theano.config.floatX,
(False, False)))
myManualNestedType1 = TypedListType(TypedListType(
TypedListType(myType)))
myManualNestedType2 = TypedListType(TypedListType(myType))
self.assertFalse(myManualNestedType1 == myManualNestedType2)
self.assertFalse(myManualNestedType2 == myManualNestedType1)
def test_variable_is_Typed_List_variable(self):
mySymbolicVariable = TypedListType(
T.TensorType(theano.config.floatX, (False, False))
)()
assert isinstance(mySymbolicVariable, theano.typed_list.TypedListVariable)
