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b9f8f863d9
* update model id * codec_model eval * add processor img * use ungated repo for processor tests
140 lines
6.9 KiB
Python
140 lines
6.9 KiB
Python
# 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 json
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import shutil
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import tempfile
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import unittest
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import jinja2
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import numpy as np
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from transformers import CsmProcessor
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from transformers.testing_utils import require_torch
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from transformers.utils import is_torch_available
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from ...test_processing_common import ProcessorTesterMixin
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if is_torch_available():
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import torch
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@require_torch
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class CsmProcessorTest(ProcessorTesterMixin, unittest.TestCase):
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processor_class = CsmProcessor
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@classmethod
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def setUpClass(cls):
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cls.checkpoint = "hf-internal-testing/namespace-sesame-repo_name_csm-1b"
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processor = CsmProcessor.from_pretrained(cls.checkpoint)
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cls.audio_token = processor.audio_token
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cls.audio_token_id = processor.audio_token_id
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cls.pad_token_id = processor.tokenizer.pad_token_id
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cls.bos_token_id = processor.tokenizer.bos_token_id
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cls.tmpdirname = tempfile.mkdtemp()
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processor.save_pretrained(cls.tmpdirname)
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@classmethod
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def tearDownClass(cls):
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shutil.rmtree(cls.tmpdirname, ignore_errors=True)
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def prepare_processor_dict(self):
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return {"chat_template": "\n{%- for message in messages %}\n {#-- Validate role is a stringified integer --#}\n {%- if not message['role'] is string or not message['role'].isdigit() %}\n {{- raise_exception(\"The role must be an integer or a stringified integer (e.g. '0') designating the speaker id\") }}\n {%- endif %}\n\n {#-- Validate content is a list --#}\n {%- set content = message['content'] %}\n {%- if content is not iterable or content is string %}\n {{- raise_exception(\"The content must be a list\") }}\n {%- endif %}\n\n {#-- Collect content types --#}\n {%- set content_types = content | map(attribute='type') | list %}\n {%- set is_last = loop.last %}\n\n {#-- Last message validation --#}\n {%- if is_last %}\n {%- if 'text' not in content_types %}\n {{- raise_exception(\"The last message must include one item of type 'text'\") }}\n {%- elif (content_types | select('equalto', 'text') | list | length > 1) or (content_types | select('equalto', 'audio') | list | length > 1) %}\n {{- raise_exception(\"At most two items are allowed in the last message: one 'text' and one 'audio'\") }}\n {%- endif %}\n\n {#-- All other messages validation --#}\n {%- else %}\n {%- if content_types | select('equalto', 'text') | list | length != 1\n or content_types | select('equalto', 'audio') | list | length != 1 %}\n {{- raise_exception(\"Each message (except the last) must contain exactly one 'text' and one 'audio' item\") }}\n {%- elif content_types | reject('in', ['text', 'audio']) | list | length > 0 %}\n {{- raise_exception(\"Only 'text' and 'audio' types are allowed in content\") }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n\n{%- for message in messages %}\n {{- bos_token }}\n {{- '[' + message['role'] + ']' }}\n {{- message['content'][0]['text'] }}\n {{- eos_token }}\n {%- if message['content']|length > 1 %}\n {{- '<|AUDIO|><|audio_eos|>' }}\n {%- endif %}\n{%- endfor %}\n"} # fmt: skip
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def test_chat_template_is_saved(self):
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processor_loaded = self.processor_class.from_pretrained(self.tmpdirname)
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processor_dict_loaded = json.loads(processor_loaded.to_json_string())
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# chat templates aren't serialized to json in processors
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self.assertFalse("chat_template" in processor_dict_loaded.keys())
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# they have to be saved as separate file and loaded back from that file
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# so we check if the same template is loaded
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processor_dict = self.prepare_processor_dict()
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self.assertTrue(processor_loaded.chat_template == processor_dict.get("chat_template", None))
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def test_apply_chat_template(self):
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# Message contains content which a mix of lists with images and image urls and string
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messages = [
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{
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"role": "0",
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"content": [
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{"type": "text", "text": "This is a test sentence 0."},
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{"type": "audio"},
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],
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},
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{
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"role": "1",
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"content": [
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{"type": "text", "text": "This is a test sentence 1."},
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{"type": "audio"},
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],
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},
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{
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"role": "0",
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"content": [
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{"type": "text", "text": "This is a prompt."},
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],
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},
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]
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processor = CsmProcessor.from_pretrained(self.tmpdirname)
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rendered = processor.apply_chat_template(messages, tokenize=False)
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expected_rendered = (
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"<|begin_of_text|>[0]This is a test sentence 0.<|end_of_text|>"
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"<|AUDIO|><|audio_eos|>"
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"<|begin_of_text|>[1]This is a test sentence 1.<|end_of_text|>"
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"<|AUDIO|><|audio_eos|>"
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"<|begin_of_text|>[0]This is a prompt.<|end_of_text|>"
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)
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self.assertEqual(rendered, expected_rendered)
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messages = [
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{
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"role": "0",
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"content": [
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{"type": "text", "text": "This is a test sentence."},
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],
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},
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{
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"role": "1",
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"content": [
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{"type": "text", "text": "This is a test sentence."},
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],
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},
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]
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# this should raise an error because the CSM processor requires audio content in the messages expect the last one
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with self.assertRaises(jinja2.exceptions.TemplateError):
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input_ids = processor.apply_chat_template(messages, tokenize=False)
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# now let's very that it expands audio tokens correctly
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messages = [
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{
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"role": "0",
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"content": [
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{"type": "text", "text": "This is a test sentence."},
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{"type": "audio", "audio": np.zeros(4096)},
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],
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},
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]
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input_ids = processor.apply_chat_template(messages, tokenize=True)
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# 4096 audio input values should give 3 audio tokens
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expected_ids = torch.tensor(
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[[128000, 58, 15, 60, 2028, 374, 264, 1296, 11914, 13, 128001, 128002, 128002, 128002, 128003]]
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)
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torch.testing.assert_close(input_ids, expected_ids)
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