Bump python version to 3.10+, switch tflite to new ai-edge-litert

.gitignore

@@ -127,3 +127,18 @@ dmypy.json
 
 # Pyre type checker
 .pyre/
+
+# Most notebooks
+notebooks/
+!notebooks/automatic_model_training.ipynb
+!notebooks/converting_google_speech_embedding_model.ipynb
+!notebooks/performance_metrics.ipynb
+!notebooks/training_models.ipynb
+!training_tutorial_data
+
+# Most example files
+examples/
+!examples/audio/activation.wav
+
+# archive files
+archive/

openwakeword/custom_verifier_model.py

@@ -62,7 +62,7 @@ def get_reference_clip_features(
     # Get predictions
     for _ in range(N):
         # Load clip
-        if type(reference_clip) == str:
+        if isinstance(reference_clip, str):
             sr, dat = scipy.io.wavfile.read(reference_clip)
         else:
             dat = reference_clip

openwakeword/data.py

@@ -803,8 +803,8 @@ class mmap_batch_generator:
             self.n_per_class = {}
             for lbl, shape in self.shapes.items():
                 dummy_data = np.random.random((10, self.shapes[lbl][1], self.shapes[lbl][2]))
-                if self.data_transform_funcs.get(lbl, None):
-                    scale_factor = self.data_transform_funcs.get(lbl, None)(dummy_data).shape[0]/10
+                if (transform_func := self.data_transform_funcs.get(lbl, None)):
+                    scale_factor = transform_func(dummy_data).shape[0]/10
 
                 ratio = self.shapes[lbl][0]/sum([i[0] for i in self.shapes.values()])
                 self.n_per_class[lbl] = max(1, int(int(batch_size*ratio)/scale_factor))

openwakeword/model.py

@@ -111,7 +111,7 @@ class Model():
         # Do imports for  inference framework
         if inference_framework == "tflite":
             try:
-                import tflite_runtime.interpreter as tflite
+                import ai_edge_litert.interpreter as tflite
 
                 def tflite_predict(tflite_interpreter, input_index, output_index, x):
                     tflite_interpreter.set_tensor(input_index, x)
@@ -127,8 +127,8 @@ class Model():
                     inference_framework = "onnx"
                     wakeword_models = [i.replace('.tflite', '.onnx') for i in wakeword_models]
                 else:
-                    raise ValueError("Tried to import the tflite runtime for provided tflite models, but it was not found. "
-                                     "Please install it using `pip install tflite-runtime`")
+                    raise ValueError("Tried to import the LiteRT runtime for provided LiteRT models, but it was not found. "
+                                     "Please install it using `pip install ai-edge-litert`")
 
         if inference_framework == "onnx":
             try:

openwakeword/utils.py

@@ -94,10 +94,10 @@ class AudioFeatures():
 
         elif inference_framework == "tflite":
             try:
-                import tflite_runtime.interpreter as tflite
+                import ai_edge_litert.interpreter as tflite
             except ImportError:
-                raise ValueError("Tried to import the TFLite runtime, but it was not found."
-                                 "Please install it using `pip install tflite-runtime`")
+                raise ValueError("Tried to import the LiteRT runtime, but it was not found."
+                                 "Please install it using `pip install ai-edge-litert`")
 
             if melspec_model_path == "":
                 melspec_model_path = os.path.join(pathlib.Path(__file__).parent.resolve(),

pyproject.toml

@@ -18,7 +18,7 @@ authors = [
 ]
 description = "An open-source audio wake word (or phrase) detection framework with a focus on performance and simplicity"
 readme = "README.md"
-requires-python = ">=3.7"
+requires-python = ">=3.10"
 classifiers = [
     "Programming Language :: Python :: 3",
     "License :: OSI Approved :: Apache Software License",

setup.py

@@ -4,19 +4,20 @@ import setuptools
 with open("README.md", "r", encoding="utf-8") as fh:
     long_description = fh.read()
 
+
 # Build extras_requires based on platform
 def build_additional_requires():
-    py_version = platform.python_version()[0:3].replace('.', "")
-    if platform.system() == "Linux" and platform.machine() == "x86_64":
-        additional_requires=[
-            f"speexdsp_ns @ https://github.com/dscripka/openWakeWord/releases/download/v0.1.1/speexdsp_ns-0.1.2-cp{py_version}-cp{py_version}-linux_x86_64.whl",
-        ]
-    elif platform.system() == "Linux" and platform.machine() == "aarch64":
-        additional_requires=[
-            f"speexdsp_ns @ https://github.com/dscripka/openWakeWord/releases/download/v0.1.1/speexdsp_ns-0.1.2-cp{py_version}-cp{py_version}-linux_aarch64.whl",
-        ],
-    elif platform.system() == "Windows" and platform.machine() == "x86_64":
-        additional_requires=[
+    # py_version = platform.python_version()[0:3].replace('.', "")
+    # if platform.system() == "Linux" and platform.machine() == "x86_64":
+    #     additional_requires=[
+    #         f"speexdsp_ns @ https://github.com/dscripka/openWakeWord/releases/download/v0.1.1/speexdsp_ns-0.1.2-cp{py_version}-cp{py_version}-linux_x86_64.whl",
+    #     ]
+    # elif platform.system() == "Linux" and platform.machine() == "aarch64":
+    #     additional_requires=[
+    #         f"speexdsp_ns @ https://github.com/dscripka/openWakeWord/releases/download/v0.1.1/speexdsp_ns-0.1.2-cp{py_version}-cp{py_version}-linux_aarch64.whl",
+    #     ],
+    if platform.system() == "Windows" and platform.machine() == "x86_64":
+        additional_requires = [
             'PyAudioWPatch'
         ]
     else:
@@ -24,12 +25,14 @@ def build_additional_requires():
 
     return additional_requires
 
+
 setuptools.setup(
     name="openwakeword",
     version="0.6.0",
     install_requires=[
         'onnxruntime>=1.10.0,<2',
-        'tflite-runtime>=2.8.0,<3; platform_system == "Linux"',
+        'ai-edge-litert>=2.0.2,<3; platform_system == "Linux" or platform_system == "Darwin"',
+        'speexdsp-ns>=0.1.2,<1; platform_system == "Linux"',
         'tqdm>=4.0,<5.0',
         'scipy>=1.3,<2',
         'scikit-learn>=1,<2',
@@ -40,7 +43,7 @@ setuptools.setup(
                     'pytest>=7.2.0,<8',
                     'pytest-cov>=2.10.1,<3',
                     'pytest-flake8>=1.1.1,<2',
-                    'flake8>=4.0,<4.1',
+                    'flake8>=5.0,<7.1',
                     'pytest-mypy>=0.10.0,<1',
                     'types-requests',
                     'types-PyYAML',
@@ -90,5 +93,5 @@ setuptools.setup(
     ],
     packages=setuptools.find_packages(),
     include_package_data=True,
-    python_requires=">=3.7",
+    python_requires=">=3.10",
 )

tests/test_models.py

@@ -53,12 +53,17 @@ class TestModels:
                                         os.path.join("openwakeword", "resources", "models", "alexa_v0.1.onnx")
                                       ], inference_framework="onnx")
 
+        # Prediction on random data
+        prediction = owwModel.predict(np.random.randint(-1000, 1000, 1280).astype(np.int16))
+        assert prediction["alexa_v0.1"] >= 0 and prediction["alexa_v0.1"] <= 1
+
         owwModel = openwakeword.Model(wakeword_models=[
                                         os.path.join("openwakeword", "resources", "models", "alexa_v0.1.tflite")
                                       ], inference_framework="tflite")
 
         # Prediction on random data
-        owwModel.predict(np.random.randint(-1000, 1000, 1280).astype(np.int16))
+        prediction = owwModel.predict(np.random.randint(-1000, 1000, 1280).astype(np.int16))
+        assert prediction["alexa_v0.1"] >= 0 and prediction["alexa_v0.1"] <= 1
 
     def test_predict_with_different_frame_sizes(self):
         # Test with binary model