65 lines
		
	
	
		
			2.1 KiB
		
	
	
	
		
			Python
		
	
	
	
			
		
		
	
	
			65 lines
		
	
	
		
			2.1 KiB
		
	
	
	
		
			Python
		
	
	
	
| # coding=utf-8
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| # Copyright 2024 HuggingFace Inc.
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| #
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| # Licensed under the Apache License, Version 2.0 (the "License");
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| # you may not use this file except in compliance with the License.
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| # You may obtain a copy of the License at
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| #
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| #     http://www.apache.org/licenses/LICENSE-2.0
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| #
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| # Unless required by applicable law or agreed to in writing, software
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| # distributed under the License is distributed on an "AS IS" BASIS,
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| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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| # See the License for the specific language governing permissions and
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| # limitations under the License.
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| 
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| import unittest
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| from pathlib import Path
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| 
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| import numpy as np
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| from PIL import Image
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| 
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| from transformers import is_torch_available
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| from transformers.testing_utils import get_tests_dir, require_torch
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| from smolagents.types import AGENT_TYPE_MAPPING
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| 
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| from smolagents.default_tools import FinalAnswerTool
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| 
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| from .test_tools import ToolTesterMixin
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| 
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| 
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| if is_torch_available():
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|     import torch
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| 
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| 
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| class FinalAnswerToolTester(unittest.TestCase, ToolTesterMixin):
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|     def setUp(self):
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|         self.inputs = {"answer": "Final answer"}
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|         self.tool = FinalAnswerTool()
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| 
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|     def test_exact_match_arg(self):
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|         result = self.tool("Final answer")
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|         self.assertEqual(result, "Final answer")
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| 
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|     def test_exact_match_kwarg(self):
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|         result = self.tool(answer=self.inputs["answer"])
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|         self.assertEqual(result, "Final answer")
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| 
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|     def create_inputs(self):
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|         inputs_text = {"answer": "Text input"}
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|         inputs_image = {
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|             "answer": Image.open(
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|                 Path(get_tests_dir("fixtures")) / "000000039769.png"
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|             ).resize((512, 512))
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|         }
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|         inputs_audio = {"answer": torch.Tensor(np.ones(3000))}
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|         return {"string": inputs_text, "image": inputs_image, "audio": inputs_audio}
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| 
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|     @require_torch
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|     def test_agent_type_output(self):
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|         inputs = self.create_inputs()
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|         for input_type, input in inputs.items():
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|             output = self.tool(**input, sanitize_inputs_outputs=True)
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|             agent_type = AGENT_TYPE_MAPPING[input_type]
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|             self.assertTrue(isinstance(output, agent_type))
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