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