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110 lines
4.4 KiB
Python
110 lines
4.4 KiB
Python
# Copyright 2024 The HuggingFace Team. All rights reserved.
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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 transformers import AutoTokenizer, Qwen2AudioProcessor
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from transformers.testing_utils import require_torch, require_torchaudio
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from ...test_processing_common import ProcessorTesterMixin, url_to_local_path
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@require_torch
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@require_torchaudio
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class Qwen2AudioProcessorTest(ProcessorTesterMixin, unittest.TestCase):
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processor_class = Qwen2AudioProcessor
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tiny_model_id = "hf-internal-testing/tiny-processor-qwen2_audio"
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model_id = "Qwen/Qwen2-Audio-7B-Instruct"
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@classmethod
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def _setup_test_attributes(cls, processor):
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cls.audio_token = processor.audio_token
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def test_can_load_various_tokenizers(self):
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processor = Qwen2AudioProcessor.from_pretrained(self.tmpdirname)
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tokenizer = AutoTokenizer.from_pretrained(self.tmpdirname)
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self.assertEqual(processor.tokenizer.__class__, tokenizer.__class__)
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def test_tokenizer_integration(self):
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slow_tokenizer = AutoTokenizer.from_pretrained(self.full_tmpdirname, use_fast=False)
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fast_tokenizer = AutoTokenizer.from_pretrained(self.full_tmpdirname, from_slow=True, legacy=False)
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prompt = "<|im_start|>system\nAnswer the questions.<|im_end|><|im_start|>user\n<|audio_bos|><|AUDIO|><|audio_eos|>\nWhat is it in this audio?<|im_end|><|im_start|>assistant\n"
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EXPECTED_OUTPUT = [
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"<|im_start|>",
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"system",
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"Ċ",
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"Answer",
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"Ġthe",
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"Ġquestions",
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".",
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"<|im_end|>",
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"<|im_start|>",
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"user",
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"Ċ",
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"<|audio_bos|>",
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"<|AUDIO|>",
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"<|audio_eos|>",
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"Ċ",
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"What",
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"Ġis",
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"Ġit",
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"Ġin",
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"Ġthis",
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"Ġaudio",
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"?",
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"<|im_end|>",
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"<|im_start|>",
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"assistant",
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"Ċ",
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]
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self.assertEqual(slow_tokenizer.tokenize(prompt), EXPECTED_OUTPUT)
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self.assertEqual(fast_tokenizer.tokenize(prompt), EXPECTED_OUTPUT)
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def test_chat_template(self):
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processor = self.get_processor(use_tiny_ckpt=False)
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expected_prompt = "<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n<|im_start|>user\nAudio 1: <|audio_bos|><|AUDIO|><|audio_eos|>\nWhat's that sound?<|im_end|>\n<|im_start|>assistant\nIt is the sound of glass shattering.<|im_end|>\n<|im_start|>user\nAudio 2: <|audio_bos|><|AUDIO|><|audio_eos|>\nHow about this one?<|im_end|>\n<|im_start|>assistant\n"
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messages = [
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{"role": "system", "content": "You are a helpful assistant."},
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{
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"role": "user",
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"content": [
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{
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"type": "audio",
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"audio_url": url_to_local_path(
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"https://huggingface.co/datasets/raushan-testing-hf/audio-test/resolve/main/glass-breaking-151256.mp3"
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),
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},
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{"type": "text", "text": "What's that sound?"},
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],
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},
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{"role": "assistant", "content": "It is the sound of glass shattering."},
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{
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"role": "user",
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"content": [
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{
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"type": "audio",
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"audio_url": url_to_local_path(
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"https://huggingface.co/datasets/raushan-testing-hf/audio-test/resolve/main/f2641_0_throatclearing.wav"
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),
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},
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{"type": "text", "text": "How about this one?"},
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],
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},
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]
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formatted_prompt = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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self.assertEqual(expected_prompt, formatted_prompt)
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