def test_recappl(self):
batsize = 100
self.dims = [50, 20, 30, 40]
recstack = RecStack(*[GRU(dim=self.dims[i], innerdim=self.dims[i+1]) for i in range(len(self.dims)-1)])
mu = RecPredictor(recstack)
for i in range(3):
inpval = np.random.random((batsize, 50)).astype("float32")
outpvals = mu.feed(inpval)
self.assertEqual(outpvals.shape, (batsize, self.dims[-1]))
def test_recappl_shapes_model_user(self):
batsize = 100
model = SimpleSeqTransDec(indim=200, outdim=50, inpembdim=20, outembdim=20, innerdim=[40, 30])
mu = RecPredictor(model)
inpval2 = np.random.randint(0, 50, (batsize,)).astype("int32")
for i in range(5):
inpval = np.random.randint(0, 200, (batsize,)).astype("int32")
outpval = mu.feed(inpval, inpval2)
inpval2 = np.argmax(outpval, axis=1).astype("int32")
self.assertEqual(outpval.shape, (batsize, 50))
def test_recappl(self):
batsize = 100
self.dims = [50, 20, 30, 40]
recstack = RecStack(*[
GRU(dim=self.dims[i], innerdim=self.dims[i + 1])
for i in range(len(self.dims) - 1)
])
mu = RecPredictor(recstack)
for i in range(3):
inpval = np.random.random((batsize, 50)).astype("float32")
outpvals = mu.feed(inpval)
self.assertEqual(outpvals.shape, (batsize, self.dims[-1]))
def test_recappl_shapes_model_user(self):
batsize = 100
model = SimpleSeqTransDec(indim=200,
outdim=50,
inpembdim=20,
outembdim=20,
innerdim=[40, 30])
mu = RecPredictor(model)
inpval2 = np.random.randint(0, 50, (batsize, )).astype("int32")
for i in range(5):
inpval = np.random.randint(0, 200, (batsize, )).astype("int32")
outpval = mu.feed(inpval, inpval2)
inpval2 = np.argmax(outpval, axis=1).astype("int32")
self.assertEqual(outpval.shape, (batsize, 50))
def __init__(self, model, beamsize=1, *buildargs, **kw):
super(Searcher, self).__init__(**kw)
self.beamsize = beamsize
self.model = model
self.mu = RecPredictor(model, *buildargs)
