(self)
| 32 | class InterpreterTest(test_util.TensorFlowTestCase): |
| 33 | |
| 34 | def testFloat(self): |
| 35 | interpreter = interpreter_wrapper.Interpreter( |
| 36 | model_path=resource_loader.get_path_to_datafile( |
| 37 | 'testdata/permute_float.tflite')) |
| 38 | interpreter.allocate_tensors() |
| 39 | |
| 40 | input_details = interpreter.get_input_details() |
| 41 | self.assertEqual(1, len(input_details)) |
| 42 | self.assertEqual('input', input_details[0]['name']) |
| 43 | self.assertEqual(np.float32, input_details[0]['dtype']) |
| 44 | self.assertTrue(([1, 4] == input_details[0]['shape']).all()) |
| 45 | self.assertEqual((0.0, 0), input_details[0]['quantization']) |
| 46 | |
| 47 | output_details = interpreter.get_output_details() |
| 48 | self.assertEqual(1, len(output_details)) |
| 49 | self.assertEqual('output', output_details[0]['name']) |
| 50 | self.assertEqual(np.float32, output_details[0]['dtype']) |
| 51 | self.assertTrue(([1, 4] == output_details[0]['shape']).all()) |
| 52 | self.assertEqual((0.0, 0), output_details[0]['quantization']) |
| 53 | |
| 54 | test_input = np.array([[1.0, 2.0, 3.0, 4.0]], dtype=np.float32) |
| 55 | expected_output = np.array([[4.0, 3.0, 2.0, 1.0]], dtype=np.float32) |
| 56 | interpreter.set_tensor(input_details[0]['index'], test_input) |
| 57 | interpreter.invoke() |
| 58 | |
| 59 | output_data = interpreter.get_tensor(output_details[0]['index']) |
| 60 | self.assertTrue((expected_output == output_data).all()) |
| 61 | |
| 62 | def testUint8(self): |
| 63 | model_path = resource_loader.get_path_to_datafile( |
nothing calls this directly
no test coverage detected