126 lines
3.9 KiB
Python
126 lines
3.9 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 os
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import tempfile
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import unittest
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import uuid
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from pathlib import Path
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from smolagents.types import AgentAudio, AgentImage, AgentText
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from transformers.testing_utils import (
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get_tests_dir,
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require_soundfile,
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require_torch,
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require_vision,
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)
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from transformers.utils import (
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is_soundfile_availble,
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)
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import torch
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from PIL import Image
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if is_soundfile_availble():
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import soundfile as sf
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def get_new_path(suffix="") -> str:
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directory = tempfile.mkdtemp()
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return os.path.join(directory, str(uuid.uuid4()) + suffix)
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@require_soundfile
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@require_torch
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class AgentAudioTests(unittest.TestCase):
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def test_from_tensor(self):
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tensor = torch.rand(12, dtype=torch.float64) - 0.5
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agent_type = AgentAudio(tensor)
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path = str(agent_type.to_string())
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# Ensure that the tensor and the agent_type's tensor are the same
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self.assertTrue(torch.allclose(tensor, agent_type.to_raw(), atol=1e-4))
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del agent_type
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# Ensure the path remains even after the object deletion
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self.assertTrue(os.path.exists(path))
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# Ensure that the file contains the same value as the original tensor
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new_tensor, _ = sf.read(path)
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self.assertTrue(torch.allclose(tensor, torch.tensor(new_tensor), atol=1e-4))
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def test_from_string(self):
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tensor = torch.rand(12, dtype=torch.float64) - 0.5
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path = get_new_path(suffix=".wav")
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sf.write(path, tensor, 16000)
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agent_type = AgentAudio(path)
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self.assertTrue(torch.allclose(tensor, agent_type.to_raw(), atol=1e-4))
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self.assertEqual(agent_type.to_string(), path)
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@require_vision
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@require_torch
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class AgentImageTests(unittest.TestCase):
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def test_from_tensor(self):
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tensor = torch.randint(0, 256, (64, 64, 3))
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agent_type = AgentImage(tensor)
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path = str(agent_type.to_string())
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# Ensure that the tensor and the agent_type's tensor are the same
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self.assertTrue(torch.allclose(tensor, agent_type._tensor, atol=1e-4))
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self.assertIsInstance(agent_type.to_raw(), Image.Image)
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# Ensure the path remains even after the object deletion
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del agent_type
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self.assertTrue(os.path.exists(path))
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def test_from_string(self):
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path = Path(get_tests_dir("fixtures/")) / "000000039769.png"
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image = Image.open(path)
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agent_type = AgentImage(path)
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self.assertTrue(path.samefile(agent_type.to_string()))
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self.assertTrue(image == agent_type.to_raw())
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# Ensure the path remains even after the object deletion
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del agent_type
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self.assertTrue(os.path.exists(path))
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def test_from_image(self):
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path = Path(get_tests_dir("fixtures/")) / "000000039769.png"
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image = Image.open(path)
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agent_type = AgentImage(image)
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self.assertFalse(path.samefile(agent_type.to_string()))
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self.assertTrue(image == agent_type.to_raw())
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# Ensure the path remains even after the object deletion
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del agent_type
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self.assertTrue(os.path.exists(path))
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class AgentTextTests(unittest.TestCase):
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def test_from_string(self):
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string = "Hey!"
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agent_type = AgentText(string)
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self.assertEqual(string, agent_type.to_string())
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self.assertEqual(string, agent_type.to_raw())
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self.assertEqual(string, agent_type)
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