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))