def testSeqToKey(self):
b = builder_lib.ModelBuilderBase()
# Update features with sigmoid(padding).
p = b._SeqToKey('p', 'features', b._GetValue('get_padding', 'padding'),
b._Sigmoid('sigmoid'))
l = p.Instantiate()
x = py_utils.NestedMap({
'points': tf.constant(3.0),
'features': tf.constant(5.0),
'padding': tf.constant(0.0),
'extra_key': tf.constant(1.0),
})
y = l.FPropDefaultTheta(x)
with self.session():
actual_y = self.evaluate(y)
self.assertDictEqual(
actual_y, {
'points': np.asarray([3.0]),
'features': np.asarray([0.5]),
'padding': np.asarray([0.0]),
'extra_key': np.asarray([1.0]),
})
def testSelfAttenStack(self):
b = builder_lib.ModelBuilderBase()
p = b._SelfAttenStack('p', 6, 128, 256, 4, 0.8)
self._TestFProp(p, (4, 100, 128), (4, 100, 128))
def testAtten(self):
b = builder_lib.ModelBuilderBase()
p = b._Atten('p', 128, 256, 4, 0.8)
self._TestFProp(p, (4, 100, 128), (4, 100, 128))
def testAdd(self):
b = builder_lib.ModelBuilderBase()
p = b._Add('p', b._Seq('l'), b._Seq('r'))
self._TestFProp(p, (4, 100, 64), (4, 100, 64))
def testProject(self):
self._TestFProp(builder_lib.ModelBuilderBase()._Project('p', 64, 128),
(4, 100, 64), (4, 100, 128))
def testLN(self):
self._TestFProp(builder_lib.ModelBuilderBase()._LN('ln', 128),
(4, 100, 128), (4, 100, 128))
