134 lines
4.3 KiB
Python
134 lines
4.3 KiB
Python
# coding=utf-8
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# Copyright 2023 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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from pathlib import Path
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from typing import List
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from transformers import is_torch_available, is_vision_available
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from transformers.testing_utils import get_tests_dir, is_tool_test
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from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
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if is_torch_available():
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import torch
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if is_vision_available():
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from PIL import Image
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authorized_types = ["text", "image", "audio"]
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def create_inputs(input_types: List[str]):
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inputs = []
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for input_type in input_types:
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if input_type == "text":
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inputs.append("Text input")
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elif input_type == "image":
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inputs.append(
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Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO")) / "000000039769.png").resize((512, 512))
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)
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elif input_type == "audio":
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inputs.append(torch.ones(3000))
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elif isinstance(input_type, list):
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inputs.append(create_inputs(input_type))
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else:
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raise ValueError(f"Invalid type requested: {input_type}")
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return inputs
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def output_types(outputs: List):
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output_types = []
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for output in outputs:
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if isinstance(output, (str, AgentText)):
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output_types.append("text")
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elif isinstance(output, (Image.Image, AgentImage)):
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output_types.append("image")
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elif isinstance(output, (torch.Tensor, AgentAudio)):
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output_types.append("audio")
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else:
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raise ValueError(f"Invalid output: {output}")
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return output_types
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@is_tool_test
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class ToolTesterMixin:
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def test_inputs_outputs(self):
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self.assertTrue(hasattr(self.tool, "inputs"))
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self.assertTrue(hasattr(self.tool, "outputs"))
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inputs = self.tool.inputs
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for _input in inputs:
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if isinstance(_input, list):
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for __input in _input:
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self.assertTrue(__input in authorized_types)
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else:
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self.assertTrue(_input in authorized_types)
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outputs = self.tool.outputs
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for _output in outputs:
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self.assertTrue(_output in authorized_types)
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def test_call(self):
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inputs = create_inputs(self.tool.inputs)
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outputs = self.tool(*inputs)
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# There is a single output
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if len(self.tool.outputs) == 1:
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outputs = [outputs]
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self.assertListEqual(output_types(outputs), self.tool.outputs)
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def test_common_attributes(self):
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self.assertTrue(hasattr(self.tool, "description"))
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self.assertTrue(hasattr(self.tool, "default_checkpoint"))
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self.assertTrue(self.tool.description.startswith("This is a tool that"))
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def test_agent_types_outputs(self):
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inputs = create_inputs(self.tool.inputs)
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outputs = self.tool(*inputs)
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if not isinstance(outputs, list):
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outputs = [outputs]
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self.assertEqual(len(outputs), len(self.tool.outputs))
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for output, output_type in zip(outputs, self.tool.outputs):
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agent_type = AGENT_TYPE_MAPPING[output_type]
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self.assertTrue(isinstance(output, agent_type))
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def test_agent_types_inputs(self):
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inputs = create_inputs(self.tool.inputs)
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_inputs = []
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for _input, input_type in zip(inputs, self.tool.inputs):
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if isinstance(input_type, list):
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_inputs.append([AGENT_TYPE_MAPPING[_input_type](_input) for _input_type in input_type])
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else:
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_inputs.append(AGENT_TYPE_MAPPING[input_type](_input))
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# Should not raise an error
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outputs = self.tool(*inputs)
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if not isinstance(outputs, list):
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outputs = [outputs]
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self.assertEqual(len(outputs), len(self.tool.outputs))
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