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import numpy
import pytest
from thinc.api import NumpyOps, Ragged, registry, strings2arrays
from ..util import get_data_checker
@pytest.fixture(params=[[], [(10, 2)], [(5, 3), (1, 3)], [(2, 3), (0, 3), (1, 3)]])
def shapes(request):
return request.param
@pytest.fixture
def ops():
return NumpyOps()
@pytest.fixture
def list_data(shapes):
return [numpy.zeros(shape, dtype="f") for shape in shapes]
@pytest.fixture
def ragged_data(ops, list_data):
lengths = numpy.array([len(x) for x in list_data], dtype="i")
if not list_data:
return Ragged(ops.alloc2f(0, 0), lengths)
else:
return Ragged(ops.flatten(list_data), lengths)
@pytest.fixture
def padded_data(ops, list_data):
return ops.list2padded(list_data)
@pytest.fixture
def array_data(ragged_data):
return ragged_data.data
def check_transform(transform, in_data, out_data):
model = registry.resolve({"config": {"@layers": transform}})["config"]
input_checker = get_data_checker(in_data)
output_checker = get_data_checker(out_data)
model.initialize(in_data, out_data)
Y, backprop = model(in_data, is_train=True)
output_checker(Y, out_data)
dX = backprop(Y)
input_checker(dX, in_data)
def test_list2array(list_data, array_data):
check_transform("list2array.v1", list_data, array_data)
def test_list2ragged(list_data, ragged_data):
check_transform("list2ragged.v1", list_data, ragged_data)
def test_list2padded(list_data, padded_data):
check_transform("list2padded.v1", list_data, padded_data)
def test_ragged2list(ragged_data, list_data):
check_transform("ragged2list.v1", ragged_data, list_data)
def test_padded2list(padded_data, list_data):
check_transform("padded2list.v1", padded_data, list_data)
def test_strings2arrays():
strings = ["hello", "world"]
model = strings2arrays()
Y, backprop = model.begin_update(strings)
assert len(Y) == len(strings)
assert backprop([]) == []
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