Initial commit: FunASR Speech Recognition Toolkit

Add complete FunASR codebase including models, runtime, and documentation.

tests/test_glm_asr_vllm_sampling.py

@@ -0,0 +1,119 @@
+"""Unit tests for GLM-ASR vLLM sampling-parameter handling.
+
+These tests exercise ``GLMASRVLLMEngine.generate`` without a GPU or a real
+vLLM installation: the vLLM entry points are stubbed in ``sys.modules`` and the
+audio/encoder/engine collaborators are mocked, so only the sampling-parameter
+wiring is under test.
+"""
+
+import re
+import sys
+import types
+import unittest
+from unittest import mock
+
+
+def _install_vllm_stub():
+    """Install a minimal ``vllm`` stub whose SamplingParams records kwargs."""
+
+    captured = {}
+
+    class _RecordingSamplingParams:
+        def __init__(self, **kwargs):
+            captured.clear()
+            captured.update(kwargs)
+
+    class _EmbedsPrompt:
+        def __init__(self, **kwargs):
+            self.kwargs = kwargs
+
+    vllm_mod = types.ModuleType("vllm")
+    vllm_mod.SamplingParams = _RecordingSamplingParams
+    vllm_mod.LLM = object
+    inputs_mod = types.ModuleType("vllm.inputs")
+    inputs_mod.EmbedsPrompt = _EmbedsPrompt
+    data_mod = types.ModuleType("vllm.inputs.data")
+    data_mod.EmbedsPrompt = _EmbedsPrompt
+
+    sys.modules["vllm"] = vllm_mod
+    sys.modules["vllm.inputs"] = inputs_mod
+    sys.modules["vllm.inputs.data"] = data_mod
+    return captured
+
+
+class GLMASRSamplingParamsTest(unittest.TestCase):
+    def setUp(self):
+        self.captured = _install_vllm_stub()
+        from funasr.models.glm_asr.inference_vllm import GLMASRVLLMEngine
+
+        # Build an engine without running __init__ (no model load / GPU needed).
+        engine = GLMASRVLLMEngine.__new__(GLMASRVLLMEngine)
+        engine.device = "cpu"
+        engine._encode_audio = mock.Mock(return_value="audio_embeds")
+        engine._build_prompt_embeds = mock.Mock(
+            return_value=mock.Mock(float=lambda: "embeds")
+        )
+
+        token_out = types.SimpleNamespace(token_ids=[1, 2, 3])
+        vllm_output = types.SimpleNamespace(outputs=[token_out])
+        engine.vllm_engine = mock.Mock()
+        engine.vllm_engine.generate = mock.Mock(return_value=[vllm_output])
+        engine.tokenizer = mock.Mock()
+        engine.tokenizer.decode = mock.Mock(return_value="hello world")
+        self.engine = engine
+
+    def test_defaults_preserve_greedy_behavior(self):
+        results = self.engine.generate("a.wav")
+        self.assertEqual(results, [{"key": "a", "text": "hello world"}])
+        self.assertEqual(self.captured["temperature"], 0.0)
+        self.assertEqual(self.captured["top_p"], 1.0)
+        self.assertEqual(self.captured["top_k"], -1)
+        self.assertEqual(self.captured["repetition_penalty"], 1.0)
+        self.assertEqual(self.captured["max_tokens"], 500)
+
+    def test_caller_sampling_params_are_forwarded(self):
+        self.engine.generate(
+            "a.wav", max_new_tokens=128, temperature=0.7, top_p=0.9, top_k=20
+        )
+        self.assertEqual(self.captured["max_tokens"], 128)
+        self.assertEqual(self.captured["temperature"], 0.7)
+        self.assertEqual(self.captured["top_p"], 0.9)
+        self.assertEqual(self.captured["top_k"], 20)
+
+    def test_non_positive_top_k_is_normalized_to_disabled(self):
+        self.engine.generate("a.wav", top_k=0)
+        self.assertEqual(self.captured["top_k"], -1)
+
+    def test_repetition_penalty_is_forced_neutral_in_prompt_embeds_mode(self):
+        # A non-neutral repetition_penalty would crash vLLM prompt-embeds mode
+        # (issue #2948), so it must be coerced back to 1.0 rather than forwarded.
+        self.engine.generate("a.wav", repetition_penalty=1.3)
+        self.assertEqual(self.captured["repetition_penalty"], 1.0)
+
+    def test_neutral_repetition_penalty_passes_through(self):
+        self.engine.generate("a.wav", repetition_penalty=1.0)
+        self.assertEqual(self.captured["repetition_penalty"], 1.0)
+
+
+class SafeRepetitionPenaltyTest(unittest.TestCase):
+    def setUp(self):
+        _install_vllm_stub()
+        import funasr.models.glm_asr.inference_vllm as mod
+
+        self.mod = mod
+        # Reset the process-wide warn-once flag between tests.
+        mod._warned_rep_penalty = False
+
+    def test_neutral_and_none_map_to_one(self):
+        self.assertEqual(self.mod._safe_repetition_penalty(1.0), 1.0)
+        self.assertEqual(self.mod._safe_repetition_penalty(None), 1.0)
+
+    def test_non_neutral_is_coerced_and_warns_once(self):
+        with self.assertLogs(self.mod.logger, level="WARNING") as cm:
+            self.assertEqual(self.mod._safe_repetition_penalty(1.5), 1.0)
+        self.assertTrue(any("2948" in line for line in cm.output))
+        self.assertTrue(self.mod._warned_rep_penalty)
+
+
+if __name__ == "__main__":
+    unittest.main()