72 lines
2.4 KiB
Python
72 lines
2.4 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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import unittest
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from pathlib import Path
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import numpy as np
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from PIL import Image
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from transformers import is_torch_available, load_tool
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from transformers.agents.agent_types import AGENT_TYPE_MAPPING
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from transformers.testing_utils import get_tests_dir, require_torch
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from .test_tools_common import ToolTesterMixin
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if is_torch_available():
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import torch
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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 = load_tool("final_answer")
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self.tool.setup()
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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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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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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(Path(get_tests_dir("fixtures/tests_samples/COCO")) / "000000039769.png").resize(
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(512, 512)
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)
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}
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inputs_audio = {"answer": torch.Tensor(np.ones(3000))}
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return {"text": inputs_text, "image": inputs_image, "audio": inputs_audio}
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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)
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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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@require_torch
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def test_agent_types_inputs(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)
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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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