Aston-xMAD's picture
init commit
b37c16f verified
raw
history blame
4.35 kB
# coding=utf-8
# Copyright 2023 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_torch_available():
import torch
if is_vision_available():
from PIL import Image
authorized_types = ["text", "image", "audio"]
def create_inputs(input_types: List[str]):
inputs = []
for input_type in input_types:
if input_type == "text":
inputs.append("Text input")
elif input_type == "image":
inputs.append(
Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO")) / "000000039769.png").resize((512, 512))
)
elif input_type == "audio":
inputs.append(torch.ones(3000))
elif isinstance(input_type, list):
inputs.append(create_inputs(input_type))
else:
raise ValueError(f"Invalid type requested: {input_type}")
return inputs
def output_types(outputs: List):
output_types = []
for output in outputs:
if isinstance(output, (str, AgentText)):
output_types.append("text")
elif isinstance(output, (Image.Image, AgentImage)):
output_types.append("image")
elif isinstance(output, (torch.Tensor, AgentAudio)):
output_types.append("audio")
else:
raise ValueError(f"Invalid output: {output}")
return output_types
@is_tool_test
class ToolTesterMixin:
def test_inputs_outputs(self):
self.assertTrue(hasattr(self.tool, "inputs"))
self.assertTrue(hasattr(self.tool, "outputs"))
inputs = self.tool.inputs
for _input in inputs:
if isinstance(_input, list):
for __input in _input:
self.assertTrue(__input in authorized_types)
else:
self.assertTrue(_input in authorized_types)
outputs = self.tool.outputs
for _output in outputs:
self.assertTrue(_output in authorized_types)
def test_call(self):
inputs = create_inputs(self.tool.inputs)
outputs = self.tool(*inputs)
# There is a single output
if len(self.tool.outputs) == 1:
outputs = [outputs]
self.assertListEqual(output_types(outputs), self.tool.outputs)
def test_common_attributes(self):
self.assertTrue(hasattr(self.tool, "description"))
self.assertTrue(hasattr(self.tool, "default_checkpoint"))
self.assertTrue(self.tool.description.startswith("This is a tool that"))
def test_agent_types_outputs(self):
inputs = create_inputs(self.tool.inputs)
outputs = self.tool(*inputs)
if not isinstance(outputs, list):
outputs = [outputs]
self.assertEqual(len(outputs), len(self.tool.outputs))
for output, output_type in zip(outputs, self.tool.outputs):
agent_type = AGENT_TYPE_MAPPING[output_type]
self.assertTrue(isinstance(output, agent_type))
def test_agent_types_inputs(self):
inputs = create_inputs(self.tool.inputs)
_inputs = []
for _input, input_type in zip(inputs, self.tool.inputs):
if isinstance(input_type, list):
_inputs.append([AGENT_TYPE_MAPPING[_input_type](_input) for _input_type in input_type])
else:
_inputs.append(AGENT_TYPE_MAPPING[input_type](_input))
# Should not raise an error
outputs = self.tool(*inputs)
if not isinstance(outputs, list):
outputs = [outputs]
self.assertEqual(len(outputs), len(self.tool.outputs))