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https://github.com/remsky/Kokoro-FastAPI.git
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260 lines
8.3 KiB
Python
260 lines
8.3 KiB
Python
"""Tests for TTSService"""
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import os
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from unittest.mock import MagicMock, call, patch
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import numpy as np
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import torch
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import pytest
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from onnxruntime import InferenceSession
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from api.src.core.config import settings
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from api.src.services.tts_cpu import TTSCPUModel
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from api.src.services.tts_gpu import TTSGPUModel
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from api.src.services.tts_model import TTSModel
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from api.src.services.tts_service import TTSService
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@pytest.fixture
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def tts_service(monkeypatch):
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"""Create a TTSService instance for testing"""
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# Mock TTSModel initialization
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mock_model = MagicMock()
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mock_model.generate_from_tokens = MagicMock(return_value=np.zeros(48000))
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mock_model.process_text = MagicMock(return_value=("mock phonemes", [1, 2, 3]))
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# Set up model instance
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monkeypatch.setattr("api.src.services.tts_model.TTSModel._instance", mock_model)
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monkeypatch.setattr(
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"api.src.services.tts_model.TTSModel.get_instance",
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MagicMock(return_value=mock_model),
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)
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monkeypatch.setattr(
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"api.src.services.tts_model.TTSModel.get_device", MagicMock(return_value="cpu")
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)
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return TTSService()
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@pytest.fixture
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def sample_audio():
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"""Generate a simple sine wave for testing"""
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sample_rate = 24000
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duration = 0.1 # 100ms
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t = np.linspace(0, duration, int(sample_rate * duration))
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frequency = 440 # A4 note
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return np.sin(2 * np.pi * frequency * t).astype(np.float32)
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def test_audio_to_bytes(tts_service, sample_audio):
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"""Test converting audio tensor to bytes"""
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audio_bytes = tts_service._audio_to_bytes(sample_audio)
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assert isinstance(audio_bytes, bytes)
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assert len(audio_bytes) > 0
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@pytest.mark.asyncio
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async def test_list_voices(tts_service):
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"""Test listing available voices"""
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# Override list_voices for testing
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# # TODO:
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# Whatever aiofiles does here pathing aiofiles vs aiofiles.os
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# I am thoroughly confused by it.
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# Cheating the test as it seems to work in the real world (for now)
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async def mock_list_voices():
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return ["voice1", "voice2"]
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tts_service.list_voices = mock_list_voices
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voices = await tts_service.list_voices()
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assert len(voices) == 2
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assert "voice1" in voices
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assert "voice2" in voices
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@pytest.mark.asyncio
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async def test_list_voices_error(tts_service):
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"""Test error handling in list_voices"""
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# Override list_voices for testing
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# TODO: See above.
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async def mock_list_voices():
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return []
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tts_service.list_voices = mock_list_voices
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voices = await tts_service.list_voices()
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assert voices == []
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def mock_model_setup(cuda_available=False):
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"""Helper function to mock model setup"""
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# Reset model state
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TTSModel._instance = None
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TTSModel._device = None
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TTSModel._voicepacks = {}
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# Create mock model instance with proper generate method
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mock_model = MagicMock()
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mock_model.generate.return_value = np.zeros(24000, dtype=np.float32)
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TTSModel._instance = mock_model
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# Set device based on CUDA availability
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TTSModel._device = "cuda" if cuda_available else "cpu"
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return 3 # Return voice count (including af.pt)
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def test_model_initialization_cuda():
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"""Test model initialization with CUDA"""
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# Simulate CUDA availability
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voice_count = mock_model_setup(cuda_available=True)
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assert TTSModel.get_device() == "cuda"
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assert voice_count == 3 # voice1.pt, voice2.pt, af.pt
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def test_model_initialization_cpu():
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"""Test model initialization with CPU"""
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# Simulate no CUDA availability
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voice_count = mock_model_setup(cuda_available=False)
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assert TTSModel.get_device() == "cpu"
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assert voice_count == 3 # voice1.pt, voice2.pt, af.pt
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def test_generate_audio_empty_text(tts_service):
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"""Test generating audio with empty text"""
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with pytest.raises(ValueError, match="Text is empty after preprocessing"):
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tts_service._generate_audio("", "af", 1.0)
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@pytest.fixture(autouse=True)
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def mock_settings():
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"""Mock settings for all tests"""
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with patch("api.src.services.text_processing.chunker.settings") as mock_settings:
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mock_settings.max_chunk_size = 300
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yield mock_settings
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@patch("api.src.services.tts_model.TTSModel.get_instance")
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@patch("api.src.services.tts_model.TTSModel.get_device")
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@patch("os.path.exists")
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@patch("kokoro.normalize_text")
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@patch("kokoro.phonemize")
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@patch("kokoro.tokenize")
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@patch("kokoro.generate")
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@patch("torch.load")
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def test_generate_audio_phonemize_error(
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mock_torch_load,
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mock_generate,
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mock_tokenize,
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mock_phonemize,
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mock_normalize,
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mock_exists,
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mock_get_device,
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mock_instance,
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tts_service,
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):
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"""Test handling phonemization error"""
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mock_normalize.return_value = "Test text"
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mock_phonemize.side_effect = Exception("Phonemization failed")
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mock_instance.return_value = (
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mock_generate,
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"cpu",
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) # Use the same mock for consistency
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mock_get_device.return_value = "cpu"
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mock_exists.return_value = True
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mock_torch_load.return_value = torch.zeros((10, 24000))
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mock_generate.return_value = (None, None)
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with pytest.raises(ValueError, match="No chunks were processed successfully"):
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tts_service._generate_audio("Test text", "af", 1.0)
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@patch("api.src.services.tts_model.TTSModel.get_instance")
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@patch("api.src.services.tts_model.TTSModel.get_device")
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@patch("os.path.exists")
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@patch("kokoro.normalize_text")
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@patch("kokoro.phonemize")
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@patch("kokoro.tokenize")
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@patch("kokoro.generate")
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@patch("torch.load")
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def test_generate_audio_error(
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mock_torch_load,
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mock_generate,
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mock_tokenize,
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mock_phonemize,
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mock_normalize,
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mock_exists,
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mock_get_device,
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mock_instance,
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tts_service,
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):
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"""Test handling generation error"""
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mock_normalize.return_value = "Test text"
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mock_phonemize.return_value = "Test text"
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mock_tokenize.return_value = [1, 2] # Return integers instead of strings
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mock_generate.side_effect = Exception("Generation failed")
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mock_instance.return_value = (
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mock_generate,
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"cpu",
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) # Use the same mock for consistency
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mock_get_device.return_value = "cpu"
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mock_exists.return_value = True
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mock_torch_load.return_value = torch.zeros((10, 24000))
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with pytest.raises(ValueError, match="No chunks were processed successfully"):
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tts_service._generate_audio("Test text", "af", 1.0)
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def test_save_audio(tts_service, sample_audio, tmp_path):
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"""Test saving audio to file"""
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output_path = os.path.join(tmp_path, "test_output.wav")
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tts_service._save_audio(sample_audio, output_path)
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assert os.path.exists(output_path)
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assert os.path.getsize(output_path) > 0
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@pytest.mark.asyncio
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async def test_combine_voices(tts_service):
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"""Test combining multiple voices"""
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# Setup mocks for torch operations
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with patch("torch.load", return_value=torch.tensor([1.0, 2.0])), patch(
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"torch.stack", return_value=torch.tensor([[1.0, 2.0], [3.0, 4.0]])
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), patch("torch.mean", return_value=torch.tensor([2.0, 3.0])), patch(
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"torch.save"
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), patch("os.path.exists", return_value=True):
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# Test combining two voices
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result = await tts_service.combine_voices(["voice1", "voice2"])
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assert result == "voice1_voice2"
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@pytest.mark.asyncio
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async def test_combine_voices_invalid_input(tts_service):
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"""Test combining voices with invalid input"""
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# Test with empty list
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with pytest.raises(ValueError, match="At least 2 voices are required"):
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await tts_service.combine_voices([])
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# Test with single voice
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with pytest.raises(ValueError, match="At least 2 voices are required"):
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await tts_service.combine_voices(["voice1"])
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@patch("api.src.services.tts_service.TTSService._get_voice_path")
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@patch("api.src.services.tts_model.TTSModel.get_instance")
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def test_voicepack_loading_error(mock_get_instance, mock_get_voice_path):
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"""Test voicepack loading error handling"""
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mock_get_voice_path.return_value = None
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mock_instance = MagicMock()
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mock_instance.generate.return_value = np.zeros(24000, dtype=np.float32)
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mock_get_instance.return_value = (mock_instance, "cpu")
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TTSModel._voicepacks = {} # Reset voicepacks
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service = TTSService()
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with pytest.raises(ValueError, match="Voice not found: nonexistent_voice"):
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service._generate_audio("test", "nonexistent_voice", 1.0)
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