def noop_models():
return [
with_padded(noop()),
with_array(noop()),
with_array2d(noop()),
with_list(noop()),
with_ragged(noop())
]
def test_validation():
model = chain(Relu(10), Relu(10), with_ragged(reduce_max()), Softmax())
with pytest.raises(DataValidationError):
model.initialize(X=model.ops.alloc2f(1, 10), Y=model.ops.alloc2f(1, 10))
with pytest.raises(DataValidationError):
model.initialize(X=model.ops.alloc3f(1, 10, 1), Y=model.ops.alloc2f(1, 10))
with pytest.raises(DataValidationError):
model.initialize(X=[model.ops.alloc2f(1, 10)], Y=model.ops.alloc2f(1, 10))
def get_ragged_model():
def _trim_ragged_forward(model, Xr, is_train):
def backprop(dYr):
dY = dYr.data
dX = model.ops.alloc2f(dY.shape[0], dY.shape[1] + 1)
return Ragged(dX, dYr.lengths)
return Ragged(Xr.data[:, :-1], Xr.lengths), backprop
return with_ragged(Model("trimragged", _trim_ragged_forward))