wehub-resource-sync
117 lines
3.8 KiB
Python
117 lines
3.8 KiB
Python
# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Unit test for paddle.nn.decode (BeamSearchDecoder, etc.)
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# Target: cover BeamSearchDecoder initialization and core methods
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import unittest
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import paddle
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from paddle import nn
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class TestBeamSearchDecoder(unittest.TestCase):
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"""Test BeamSearchDecoder initialization and basic methods.
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BeamSearchDecoder is available as paddle.nn.BeamSearchDecoder.
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Attributes are beam_size, start_token, end_token (no underscore prefix).
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"""
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def setUp(self):
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paddle.disable_static()
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def test_beam_search_decoder_init(self):
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"""BeamSearchDecoder basic initialization."""
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embed = nn.Embedding(100, 32)
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cell = nn.SimpleRNNCell(32, 64)
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output_layer = nn.Linear(64, 100)
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decoder = nn.BeamSearchDecoder(
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cell=cell,
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start_token=1,
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end_token=2,
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beam_size=3,
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embedding_fn=embed,
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output_fn=output_layer,
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)
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self.assertIsNotNone(decoder)
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self.assertEqual(decoder.beam_size, 3)
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self.assertEqual(decoder.start_token, 1)
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self.assertEqual(decoder.end_token, 2)
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def test_beam_search_decoder_tile_beam(self):
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"""BeamSearchDecoder tile_beam_merge_with_batch static method."""
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embed = nn.Embedding(100, 32)
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cell = nn.SimpleRNNCell(32, 64)
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output_layer = nn.Linear(64, 100)
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decoder = nn.BeamSearchDecoder(
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cell=cell,
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start_token=1,
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end_token=2,
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beam_size=3,
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embedding_fn=embed,
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output_fn=output_layer,
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)
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x = paddle.randn([2, 5, 10], dtype='float32')
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tiled = nn.BeamSearchDecoder.tile_beam_merge_with_batch(x, beam_size=3)
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self.assertEqual(tiled.shape, [6, 5, 10])
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def test_beam_search_decoder_no_embedding_fn(self):
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"""BeamSearchDecoder without embedding_fn."""
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cell = nn.SimpleRNNCell(32, 64)
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output_layer = nn.Linear(64, 100)
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decoder = nn.BeamSearchDecoder(
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cell=cell,
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start_token=1,
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end_token=2,
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beam_size=2,
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output_fn=output_layer,
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)
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self.assertIsNotNone(decoder)
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self.assertEqual(decoder.beam_size, 2)
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class TestDynamicDecode(unittest.TestCase):
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"""Test dynamic_decode function.
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dynamic_decode is available as paddle.nn.dynamic_decode.
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"""
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def setUp(self):
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paddle.disable_static()
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def test_beam_search_decoder_with_dynamic_decode(self):
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"""Test that BeamSearchDecoder can be used with dynamic_decode."""
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embed = nn.Embedding(100, 32)
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cell = nn.SimpleRNNCell(32, 64)
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output_layer = nn.Linear(64, 100)
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decoder = nn.BeamSearchDecoder(
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cell=cell,
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start_token=1,
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end_token=2,
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beam_size=2,
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embedding_fn=embed,
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output_fn=output_layer,
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)
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# Verify decoder has the required interface for dynamic_decode
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self.assertTrue(hasattr(decoder, 'step'))
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self.assertTrue(hasattr(decoder, 'beam_size'))
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self.assertTrue(hasattr(decoder, 'start_token'))
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self.assertTrue(hasattr(decoder, 'end_token'))
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if __name__ == '__main__':
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unittest.main()
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