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# Copyright 2022 DeepMind Technologies Limited. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Tests for compiler.basis_inference."""
from absl.testing import absltest
from absl.testing import parameterized
from tracr.compiler import basis_inference
from tracr.compiler import nodes
from tracr.compiler import rasp_to_graph
from tracr.rasp import rasp
class InferBasesTest(parameterized.TestCase):
def test_arithmetic_error_logs_warning(self):
program = rasp.numerical(rasp.Map(lambda x: 1 / x, rasp.tokens))
extracted = rasp_to_graph.extract_rasp_graph(program)
vocab = {0, 1, 2}
with self.assertLogs(level="WARNING"):
basis_inference.infer_bases(
extracted.graph,
extracted.sink,
vocab,
max_seq_len=1,
)
@parameterized.parameters(({1, 2, 3}, {2, 3, 4}), ({0, 5}, {1, 6}))
def test_one_edge(self, vocab, expected_value_set):
program = rasp.categorical(rasp.Map(lambda x: x + 1, rasp.tokens))
extracted = rasp_to_graph.extract_rasp_graph(program)
basis_inference.infer_bases(
extracted.graph,
extracted.sink,
vocab,
max_seq_len=1,
)
self.assertSetEqual(
extracted.graph.nodes[program.label][nodes.VALUE_SET],
expected_value_set,
)
def test_primitive_close_to_tip(self):
intermediate = rasp.categorical(rasp.tokens + 1)
intermediate = rasp.categorical(intermediate + intermediate)
program = rasp.categorical(intermediate + rasp.indices)
extracted = rasp_to_graph.extract_rasp_graph(program)
basis_inference.infer_bases(
extracted.graph,
extracted.sink,
{0, 1},
max_seq_len=2,
)
self.assertSetEqual(
extracted.graph.nodes[program.label][nodes.VALUE_SET],
{2, 3, 4, 5},
)
self.assertSetEqual(
extracted.graph.nodes[intermediate.label][nodes.VALUE_SET],
{2, 3, 4},
)
def test_categorical_aggregate(self):
program = rasp.categorical(
rasp.Aggregate(
rasp.Select(rasp.tokens, rasp.indices, rasp.Comparison.EQ),
rasp.indices,
))
extracted = rasp_to_graph.extract_rasp_graph(program)
basis_inference.infer_bases(
extracted.graph,
extracted.sink,
{0, 1},
max_seq_len=3,
)
self.assertSetEqual(
extracted.graph.nodes[program.label][nodes.VALUE_SET],
{0, 1, 2},
)
def test_numerical_aggregate(self):
program = rasp.numerical(
rasp.Aggregate(
rasp.Select(rasp.tokens, rasp.indices, rasp.Comparison.EQ),
rasp.indices,
))
extracted = rasp_to_graph.extract_rasp_graph(program)
basis_inference.infer_bases(
extracted.graph,
extracted.sink,
{0, 1},
max_seq_len=2,
)
self.assertSetEqual(
extracted.graph.nodes[program.label][nodes.VALUE_SET],
{0, 1, 1 / 2},
)
def test_selector_width(self):
program = rasp.SelectorWidth(
rasp.Select(rasp.tokens, rasp.indices, rasp.Comparison.EQ))
extracted = rasp_to_graph.extract_rasp_graph(program)
basis_inference.infer_bases(
extracted.graph,
extracted.sink,
{0, 1},
max_seq_len=2,
)
self.assertSetEqual(
extracted.graph.nodes[program.label][nodes.VALUE_SET],
{0, 1, 2},
)
if __name__ == "__main__":
absltest.main()
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