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ts.torch_handler.unit_tests package

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ts.torch_handler.unit_tests.test_base_handler module

BaseHandler 类的基本单元测试。确保它可以加载并执行示例模型

ts.torch_handler.unit_tests.test_base_handler.handler(base_model_context)[source]
ts.torch_handler.unit_tests.test_base_handler.test_batch_handle(handler, base_model_context)[source]
ts.torch_handler.unit_tests.test_base_handler.test_inference_with_profiler_works_with_custom_initialize_method(handler, base_model_context)[source]
ts.torch_handler.unit_tests.test_base_handler.test_single_handle(handler, base_model_context)[source]

ts.torch_handler.unit_tests.test_envelopes module

BaseHandler 类的基本单元测试。确保它可以加载并执行示例模型

ts.torch_handler.unit_tests.test_envelopes.handle_fn(base_model_context)[source]
ts.torch_handler.unit_tests.test_envelopes.test_binary(base_model_context)[source]
ts.torch_handler.unit_tests.test_envelopes.test_body(handle_fn, base_model_context)[source]
ts.torch_handler.unit_tests.test_envelopes.test_json(handle_fn, base_model_context)[source]
ts.torch_handler.unit_tests.test_envelopes.test_json_batch(handle_fn, base_model_context)[source]
ts.torch_handler.unit_tests.test_envelopes.test_json_double_batch(handle_fn, base_model_context)[source]

更复杂的测试案例。确保模型可以混合(mux)多个批量并返回解混合(demux)的结果

ts.torch_handler.unit_tests.test_image_classifier module

ImageClassifier 类的基本单元测试。确保它可以加载并执行示例模型

ts.torch_handler.unit_tests.test_image_classifier.context(model_dir, model_name)[source]
ts.torch_handler.unit_tests.test_image_classifier.handler(context)[source]
ts.torch_handler.unit_tests.test_image_classifier.image_bytes()[source]
ts.torch_handler.unit_tests.test_image_classifier.model_dir(tmp_path_factory, model_name)[source]
ts.torch_handler.unit_tests.test_image_classifier.model_name()[source]
ts.torch_handler.unit_tests.test_image_classifier.test_handle(context, image_bytes, handler)[source]
ts.torch_handler.unit_tests.test_image_classifier.test_handle_explain(context, image_bytes, handler)[source]

ts.torch_handler.unit_tests.test_image_segmenter module

ImageSegmenter 类的基本单元测试。确保它可以加载并执行示例模型

ts.torch_handler.unit_tests.test_image_segmenter.context(model_dir, model_name)[source]
ts.torch_handler.unit_tests.test_image_segmenter.handler(context)[source]
ts.torch_handler.unit_tests.test_image_segmenter.image_bytes()[source]
ts.torch_handler.unit_tests.test_image_segmenter.model_dir(tmp_path_factory, model_name)[source]
ts.torch_handler.unit_tests.test_image_segmenter.model_name()[source]
ts.torch_handler.unit_tests.test_image_segmenter.test_handle(handler, context, image_bytes)[source]

ts.torch_handler.unit_tests.test_mnist_kf module

ts.torch_handler.unit_tests.test_object_detector module

ObjectDetector 类的基本单元测试。确保它可以加载并执行示例模型

ts.torch_handler.unit_tests.test_object_detector.context(model_dir, model_name)[source]
ts.torch_handler.unit_tests.test_object_detector.handler(context)[source]
ts.torch_handler.unit_tests.test_object_detector.image_bytes()[source]
ts.torch_handler.unit_tests.test_object_detector.model_dir(tmp_path_factory, model_name)[source]
ts.torch_handler.unit_tests.test_object_detector.model_name()[source]
ts.torch_handler.unit_tests.test_object_detector.test_handle(handler, context, image_bytes)[source]

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