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| 1 | +"""Exercise production KWS output handling without loading acoustic models.""" |
| 2 | + |
| 3 | +import itertools |
| 4 | +import tempfile |
| 5 | +import unittest |
| 6 | +from pathlib import Path |
| 7 | +from types import SimpleNamespace |
| 8 | +from unittest.mock import patch |
| 9 | + |
| 10 | +import torch |
| 11 | + |
| 12 | +from funasr.models.fsmn_kws.model import FsmnKWS |
| 13 | +from funasr.models.fsmn_kws_mt.model import FsmnKWSMT |
| 14 | +from funasr.models.sanm_kws.model import SanmKWS |
| 15 | +from funasr.models.sanm_kws_streaming.model import SanmKWSStreaming |
| 16 | + |
| 17 | + |
| 18 | +class FixedDecoder: |
| 19 | + def __init__(self, ctc, keywords=None, token_list=None, seg_dict=None): |
| 20 | + self.result = ctc |
| 21 | + |
| 22 | + def decode(self, encoder_out): |
| 23 | + return self.result |
| 24 | + |
| 25 | + |
| 26 | +VARIANTS = (FsmnKWS, FsmnKWSMT, SanmKWS, SanmKWSStreaming) |
| 27 | +OMITTED = object() |
| 28 | + |
| 29 | + |
| 30 | +class KwsOptionalOutputTest(unittest.TestCase): |
| 31 | + def setUp(self): |
| 32 | + self.directory = tempfile.TemporaryDirectory() |
| 33 | + self.addCleanup(self.directory.cleanup) |
| 34 | + self.patch_decoder = patch( |
| 35 | + "funasr.utils.kws_utils.KwsCtcPrefixDecoder", FixedDecoder |
| 36 | + ) |
| 37 | + self.patch_decoder.start() |
| 38 | + self.addCleanup(self.patch_decoder.stop) |
| 39 | + |
| 40 | + def model(self, variant, detected=True, detected2=False): |
| 41 | + result = (detected, "wake", 0.9) |
| 42 | + model = SimpleNamespace(ctc=result, ctc2=(detected2, "hello", 0.8)) |
| 43 | + model.encode = lambda speech, lengths: (speech, lengths) |
| 44 | + if variant is FsmnKWSMT: |
| 45 | + model.encode = lambda speech, lengths: (speech, speech, lengths) |
| 46 | + model.encode_chunk = lambda speech, lengths, **kwargs: (speech, lengths) |
| 47 | + model.kws_decoder = FixedDecoder(result) |
| 48 | + self.addCleanup( |
| 49 | + lambda: model.writer.close() if hasattr(model, "writer") else None |
| 50 | + ) |
| 51 | + return model |
| 52 | + |
| 53 | + def call( |
| 54 | + self, variant, model, output_dir=OMITTED, key="sample", final=True, cache=None |
| 55 | + ): |
| 56 | + kwargs = {"device": "cpu", "data_type": "fbank", "keywords": "wake"} |
| 57 | + if output_dir is not OMITTED: |
| 58 | + kwargs["output_dir"] = output_dir |
| 59 | + speech = torch.zeros(1, 3, 1) |
| 60 | + lengths = torch.tensor([3]) |
| 61 | + tokenizer = SimpleNamespace(token_list=["wake"], seg_dict={}) |
| 62 | + if variant is FsmnKWSMT: |
| 63 | + tokenizer = [tokenizer, tokenizer] |
| 64 | + if variant is SanmKWSStreaming: |
| 65 | + if cache is None: |
| 66 | + cache = { |
| 67 | + "encoder": { |
| 68 | + "chunk_size": [0, 3, 0], |
| 69 | + "encoder_out": None, |
| 70 | + "encoder_out_lens": None, |
| 71 | + } |
| 72 | + } |
| 73 | + return variant.generate_chunk( |
| 74 | + model, |
| 75 | + speech, |
| 76 | + lengths, |
| 77 | + key=[key], |
| 78 | + tokenizer=tokenizer, |
| 79 | + cache=cache, |
| 80 | + is_final=final, |
| 81 | + **kwargs, |
| 82 | + ) |
| 83 | + results, _ = variant.inference( |
| 84 | + model, |
| 85 | + speech, |
| 86 | + data_lengths=lengths[:, None], |
| 87 | + key=[key], |
| 88 | + tokenizer=tokenizer, |
| 89 | + **kwargs, |
| 90 | + ) |
| 91 | + return results |
| 92 | + |
| 93 | + def expected(self, variant, detected=True, detected2=False, key="sample"): |
| 94 | + result = {"key": key, "text": "detected wake 0.9" if detected else "rejected"} |
| 95 | + if variant is FsmnKWSMT: |
| 96 | + result["text2"] = "detected hello 0.8" if detected2 else "rejected" |
| 97 | + return [result] |
| 98 | + |
| 99 | + def test_omitted_and_none_return_results_without_creating_writer(self): |
| 100 | + for variant, detected, detected2, output_dir in itertools.product( |
| 101 | + VARIANTS, (False, True), (False, True), (OMITTED, None) |
| 102 | + ): |
| 103 | + with self.subTest( |
| 104 | + variant=variant.__name__, |
| 105 | + detected=detected, |
| 106 | + detected2=detected2, |
| 107 | + output_dir=output_dir, |
| 108 | + ): |
| 109 | + model = self.model(variant, detected, detected2) |
| 110 | + self.assertEqual( |
| 111 | + self.call(variant, model, output_dir), |
| 112 | + self.expected(variant, detected, detected2), |
| 113 | + ) |
| 114 | + self.assertFalse(hasattr(model, "writer")) |
| 115 | + |
| 116 | + def test_enabled_output_preserves_result_and_file_format(self): |
| 117 | + for variant, detected, detected2 in itertools.product( |
| 118 | + VARIANTS, (False, True), (False, True) |
| 119 | + ): |
| 120 | + with self.subTest( |
| 121 | + variant=variant.__name__, detected=detected, detected2=detected2 |
| 122 | + ): |
| 123 | + path = ( |
| 124 | + Path(self.directory.name) |
| 125 | + / f"{variant.__name__}-{detected}-{detected2}" |
| 126 | + ) |
| 127 | + model = self.model(variant, detected, detected2) |
| 128 | + expected = self.expected(variant, detected, detected2) |
| 129 | + self.assertEqual(self.call(variant, model, str(path)), expected) |
| 130 | + self.assertEqual( |
| 131 | + (path / "detect").read_text(), f"sample {expected[0]['text']}\n" |
| 132 | + ) |
| 133 | + if variant is FsmnKWSMT: |
| 134 | + self.assertEqual( |
| 135 | + (path / "detect2").read_text(), |
| 136 | + f"sample {expected[0]['text2']}\n", |
| 137 | + ) |
| 138 | + |
| 139 | + def test_disabled_output_does_not_reuse_cached_writer(self): |
| 140 | + for variant, output_dir in itertools.product(VARIANTS, (OMITTED, None)): |
| 141 | + with self.subTest(variant=variant.__name__, output_dir=output_dir): |
| 142 | + path = ( |
| 143 | + Path(self.directory.name) |
| 144 | + / f"{variant.__name__}-{output_dir is None}" |
| 145 | + ) |
| 146 | + model = self.model(variant) |
| 147 | + self.call(variant, model, str(path), key="first") |
| 148 | + before = {p.name: p.read_bytes() for p in path.iterdir()} |
| 149 | + self.assertEqual( |
| 150 | + self.call(variant, model, output_dir, key="second"), |
| 151 | + self.expected(variant, key="second"), |
| 152 | + ) |
| 153 | + self.assertEqual( |
| 154 | + {p.name: p.read_bytes() for p in path.iterdir()}, before |
| 155 | + ) |
| 156 | + |
| 157 | + def test_consecutive_enabled_calls_append(self): |
| 158 | + for variant in VARIANTS: |
| 159 | + with self.subTest(variant=variant.__name__): |
| 160 | + path = Path(self.directory.name) / variant.__name__ |
| 161 | + model = self.model(variant) |
| 162 | + for key in ("first", "second"): |
| 163 | + self.call(variant, model, str(path), key=key) |
| 164 | + self.assertEqual( |
| 165 | + (path / "detect").read_text(), |
| 166 | + "first detected wake 0.9\nsecond detected wake 0.9\n", |
| 167 | + ) |
| 168 | + if variant is FsmnKWSMT: |
| 169 | + self.assertEqual( |
| 170 | + (path / "detect2").read_text(), |
| 171 | + "first rejected\nsecond rejected\n", |
| 172 | + ) |
| 173 | + |
| 174 | + def test_streaming_nonfinal_accumulates_and_final_returns_without_output(self): |
| 175 | + model = self.model(SanmKWSStreaming) |
| 176 | + cache = { |
| 177 | + "encoder": { |
| 178 | + "chunk_size": [0, 3, 0], |
| 179 | + "encoder_out": None, |
| 180 | + "encoder_out_lens": None, |
| 181 | + } |
| 182 | + } |
| 183 | + self.assertIsNone(self.call(SanmKWSStreaming, model, final=False, cache=cache)) |
| 184 | + self.assertFalse(hasattr(model, "writer")) |
| 185 | + self.assertEqual( |
| 186 | + self.call(SanmKWSStreaming, model, final=True, cache=cache), |
| 187 | + self.expected(SanmKWSStreaming), |
| 188 | + ) |
| 189 | + self.assertEqual(cache["encoder"]["encoder_out"].shape[1], 6) |
| 190 | + self.assertFalse(hasattr(model, "writer")) |
| 191 | + |
| 192 | + |
| 193 | +if __name__ == "__main__": |
| 194 | + unittest.main() |
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