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axolotl/tests/prompt_strategies/test_chat_templates.py
NanoCode012 10cfecf02e fix: use apply_chat_template to find turn boundaries and allow tool_calling field (#2179) [skip ci] 
* fix: use apply_chat_template to find turn boundaries and allow tool_calling field

* fix: keys to include in turn

* feat(doc): explicitly recommend setting train_on_eos and roles_to_train

* fix: eos not being masked for tool due to template padding

* chore: clear up docs

* fix: default messages format, train_on_eos: turn, and train on all assistant msg

* fix: properly warn if empty content

* feat: parametrize chat_template tests to test different tokenizers

* fix: set proper default for message key

* fix: update defaults to match load function

* fix: change defaults to use new

* feat: add tool_calling dataset

* feat: add tool_calling test

* fix: add handling of edge case of mistral tokenizer with only system prompt

* feat: refactor all test to follow source code

* fix: remove unnecessary eos_token from phi35

* fix test for phi3.5 since eos was dropped from chat_template

---------

Co-authored-by: Wing Lian <wing@axolotl.ai>
2024-12-17 16:42:21 -05:00

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"""
tests for chat_template prompt strategy
"""
import logging
import unittest
from axolotl.prompt_strategies.chat_template import (
ChatTemplatePrompter,
ChatTemplateStrategy,
load,
)
from axolotl.prompters import IGNORE_TOKEN_ID
from axolotl.utils.chat_templates import get_chat_template
from axolotl.utils.dict import DictDefault
logging.basicConfig(level=logging.DEBUG)
LOG = logging.getLogger("axolotl")
class TestAssistantChatTemplateLlama3:
"""
Test class for assistant style datasets with llama-3 prompts using the chat_template strategy.
"""
def test_llama3_load(self, llama3_tokenizer, assistant_dataset):
LOG.info("Loading llama-3 tokenizer with assistant dataset")
strategy = load(
llama3_tokenizer,
DictDefault(
{
"train_on_inputs": False,
"sequence_len": 512,
}
),
DictDefault(
{
"chat_template": "llama3",
"message_field_role": "role",
"message_field_content": "content",
"roles": {
"user": ["user"],
"assistant": ["assistant"],
"system": ["system"],
},
"field_messages": "messages",
}
),
)
res = strategy.tokenize_prompt(assistant_dataset[0])
input_ids = res["input_ids"]
# fmt: off
expected_input_ids = [
128000, # bos
128006, 882, 128007, # user header
271, 15339, 128009, # user prompt eot
128006, 78191, 128007, # assistant header
271, 15339, 128009, # assistant response eot
128006, 882, 128007,
271, 19045, 29474, 128009,
128006, 78191, 128007,
271, 19045, 29474, 128009,
]
# fmt: on
LOG.debug(f"Expected input_ids: {expected_input_ids}")
LOG.debug(f"Actual input_ids: {input_ids}")
assert (
input_ids == expected_input_ids
), f"Input IDs mismatch: {input_ids} != {expected_input_ids}"
def test_llama3(self, llama3_tokenizer, assistant_dataset):
LOG.info("Testing llama-3 with assistant dataset")
strategy = ChatTemplateStrategy(
ChatTemplatePrompter(
llama3_tokenizer,
chat_template=get_chat_template("llama3"),
message_field_role="role",
message_field_content="content",
roles={
"user": ["user"],
"assistant": ["assistant"],
"system": ["system"],
},
),
tokenizer=llama3_tokenizer,
train_on_inputs=False,
sequence_len=512,
)
strategy.messages = "messages"
res = strategy.tokenize_prompt(assistant_dataset[0])
input_ids = res["input_ids"]
# fmt: off
expected_input_ids = [
128000, # bos
128006, 882, 128007, # user header
271, 15339, 128009, # user prompt eot
128006, 78191, 128007, # assistant header
271, 15339, 128009, # assistant response eot
128006, 882, 128007,
271, 19045, 29474, 128009,
128006, 78191, 128007,
271, 19045, 29474, 128009,
]
# fmt: on
LOG.debug(f"Expected input_ids: {expected_input_ids}")
LOG.debug(f"Actual input_ids: {input_ids}")
assert (
input_ids == expected_input_ids
), f"Input IDs mismatch: {input_ids} != {expected_input_ids}"
def test_phi35(self, phi35_tokenizer, assistant_dataset):
LOG.info("Testing phi-3.5 with assistant dataset")
strategy = ChatTemplateStrategy(
ChatTemplatePrompter(
phi35_tokenizer,
chat_template=get_chat_template("phi_35"),
message_field_role="role",
message_field_content="content",
roles={
"user": ["user"],
"assistant": ["assistant"],
"system": ["system"],
},
),
tokenizer=phi35_tokenizer,
train_on_inputs=False,
sequence_len=512,
)
strategy.messages = "messages"
res = strategy.tokenize_prompt(assistant_dataset[0])
input_ids = res["input_ids"]
labels = res["labels"]
# fmt: off
expected_input_ids = [
32010, # user
22172, 32007, # user eot
32001, # assistant
22172, 32007, # assistant eot
32010, # user
1781, 26966, 32007, # user eot
32001, # assistant
1781, 26966, 32007, # assistant eot
]
expected_labels = [
-100, # user
-100, -100, # user eot
-100, # assistant
-100, -100, # assistant eot,
-100, # user
-100, -100, -100, # user eot
-100, # assistant
1781, 26966, 32007, # assistant eot
]
# fmt: on
LOG.debug(f"Expected input_ids: {expected_input_ids}")
LOG.debug(f"Actual input_ids: {input_ids}")
assert (
input_ids == expected_input_ids
), f"Input IDs mismatch: {input_ids} != {expected_input_ids}"
LOG.debug(f"Expected labels : {expected_labels}")
LOG.debug(f"Actual labels : {labels}")
assert (
labels == expected_labels
), f"Input IDs mismatch: {labels} != {expected_labels}"
def test_llama3_with_training_data(self, llama3_tokenizer, assistant_dataset):
LOG.info("Testing llama-3 with assistant dataset including training data")
strategy = ChatTemplateStrategy(
ChatTemplatePrompter(
llama3_tokenizer,
chat_template=get_chat_template("llama3"),
message_field_role="role",
message_field_content="content",
message_field_training="training",
roles={
"user": ["user"],
"assistant": ["assistant"],
"system": ["system"],
},
),
tokenizer=llama3_tokenizer,
train_on_inputs=False,
train_on_eos="none",
sequence_len=512,
roles_to_train=["assistant"],
)
strategy.messages = "messages"
prompt_tokens = strategy.prompter.build_prompt(
assistant_dataset[0]["messages"], False
)
prompt = llama3_tokenizer.decode(prompt_tokens, skip_special_tokens=False)
LOG.debug(f"Generated prompt: {prompt}")
res = strategy.tokenize_prompt(assistant_dataset[0])
labels = res["labels"]
input_ids = res["input_ids"]
# fmt: off
expected_labels = [
IGNORE_TOKEN_ID, # bos
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # user header
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # user prompt eot
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # assistant header
IGNORE_TOKEN_ID, 15339, IGNORE_TOKEN_ID, # assistant response eot
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID,
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID,
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID,
IGNORE_TOKEN_ID, 19045, 29474, IGNORE_TOKEN_ID,
]
# fmt: on
LOG.debug(f"Expected labels: {expected_labels}")
LOG.debug(f"Actual labels: {labels}")
assert labels == expected_labels, (
f"Labels mismatch:\n"
f"Expected: {expected_labels}\n"
f"Actual: {labels}\n"
f"Input IDs: {input_ids}\n"
)
class TestSharegptChatTemplateLlama3:
"""
Test class for ShareGPT style datasets with llama-3 prompts using the chat_template strategy.
"""
def test_llama3_assistant(self, llama3_tokenizer, sharegpt_dataset):
LOG.info("Testing ShareGPT style datasets with llama-3 assistant prompts")
# pylint: disable=duplicate-code
strategy = ChatTemplateStrategy(
ChatTemplatePrompter(
llama3_tokenizer,
chat_template=get_chat_template("llama3"),
message_field_role="from",
message_field_content="value",
),
tokenizer=llama3_tokenizer,
train_on_inputs=False,
train_on_eos="none",
sequence_len=512,
roles_to_train=["gpt"],
)
strategy.messages = "conversations"
res = strategy.tokenize_prompt(sharegpt_dataset[0])
input_ids = res["input_ids"]
labels = res["labels"]
# fmt: off
expected_input_ids = [
128000, # bos
128006, 882, 128007, # user header
271, 15339, 128009, # user prompt eot
128006, 78191, 128007, # assistant header
271, 15339, 128009, # assistant response eot
128006, 882, 128007,
271, 19045, 29474, 128009,
128006, 78191, 128007,
271, 19045, 29474, 128009,
]
expected_labels = [
IGNORE_TOKEN_ID, # bos
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # user header
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # user prompt eot
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # assistant header
IGNORE_TOKEN_ID, 15339, IGNORE_TOKEN_ID, # assistant response eot
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID,
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID,
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID,
IGNORE_TOKEN_ID, 19045, 29474, IGNORE_TOKEN_ID,
]
# fmt: on
LOG.debug(f"Expected input_ids: {expected_input_ids}")
LOG.debug(f"Actual input_ids: {input_ids}")
LOG.debug(f"Expected labels: {expected_labels}")
LOG.debug(f"Actual labels: {labels}")
assert (
input_ids == expected_input_ids
), f"Input IDs mismatch: {input_ids} != {expected_input_ids}"
assert (
labels == expected_labels
), f"Labels mismatch: {labels} != {expected_labels}"
def test_llama3_human(self, llama3_tokenizer, sharegpt_dataset):
LOG.info("Testing ShareGPT style datasets with llama-3 human prompts")
# pylint: disable=duplicate-code
strategy = ChatTemplateStrategy(
ChatTemplatePrompter(
llama3_tokenizer,
chat_template=get_chat_template("llama3"),
message_field_role="from",
message_field_content="value",
),
tokenizer=llama3_tokenizer,
train_on_inputs=False,
train_on_eos="none",
sequence_len=512,
roles_to_train=["human"],
)
strategy.messages = "conversations"
res = strategy.tokenize_prompt(sharegpt_dataset[0])
input_ids = res["input_ids"]
labels = res["labels"]
# fmt: off
expected_input_ids = [
128000, # bos
128006, 882, 128007, # user header
271, 15339, 128009, # user prompt eot
128006, 78191, 128007, # assistant header
271, 15339, 128009, # assistant response eot
128006, 882, 128007,
271, 19045, 29474, 128009,
128006, 78191, 128007,
271, 19045, 29474, 128009,
]
expected_labels = [
IGNORE_TOKEN_ID, # bos
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # user header
IGNORE_TOKEN_ID, 15339, IGNORE_TOKEN_ID, # user prompt eot
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # assistant header
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # assistant response eot
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID,
IGNORE_TOKEN_ID, 19045, 29474, IGNORE_TOKEN_ID,
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID,
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID,
]
# fmt: on
LOG.debug(f"Expected input_ids: {expected_input_ids}")
LOG.debug(f"Actual input_ids: {input_ids}")
LOG.debug(f"Expected labels: {expected_labels}")
LOG.debug(f"Actual labels: {labels}")
assert (
input_ids == expected_input_ids
), f"Input IDs mismatch: {input_ids} != {expected_input_ids}"
assert (
labels == expected_labels
), f"Labels mismatch: {labels} != {expected_labels}"
def test_llama3_system_human(self, llama3_tokenizer, basic_dataset):
LOG.info("Testing ShareGPT style datasets with llama-3 system/human prompts")
# pylint: disable=duplicate-code
strategy = ChatTemplateStrategy(
ChatTemplatePrompter(
llama3_tokenizer,
chat_template=get_chat_template("llama3"),
message_field_role="from",
message_field_content="value",
),
tokenizer=llama3_tokenizer,
train_on_inputs=False,
train_on_eos="none",
sequence_len=512,
roles_to_train=["system", "human"],
)
strategy.messages = "conversations"
res = strategy.tokenize_prompt(basic_dataset[0])
input_ids = res["input_ids"]
labels = res["labels"]
# fmt: off
expected_input_ids = [
128000, # bos
128006, 9125, 128007,
271, 2675, 527, 459, 15592, 18328, 13, 128009,
128006, 882, 128007, # user header
271, 9906, 128009, # user prompt eot
128006, 78191, 128007, # assistant header
271, 13347, 1070, 0, 128009, # assistant response eot
128006, 882, 128007,
271, 4438, 527, 499, 30, 128009,
128006, 78191, 128007,
271, 40, 2846, 3815, 1664, 11, 9901, 499, 0, 128009,
]
expected_labels = [
IGNORE_TOKEN_ID, # bos
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # system header
IGNORE_TOKEN_ID, 2675, 527, 459, 15592, 18328, 13, IGNORE_TOKEN_ID, # system prompt eot
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # user header
IGNORE_TOKEN_ID, 9906, IGNORE_TOKEN_ID, # user prompt eot
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # assistant header
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # assistant response eot
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID,
IGNORE_TOKEN_ID, 4438, 527, 499, 30, IGNORE_TOKEN_ID,
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID,
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID,
]
# fmt: on
LOG.debug(f"Expected input_ids: {expected_input_ids}")
LOG.debug(f"Actual input_ids: {input_ids}")
LOG.debug(f"Expected labels: {expected_labels}")
LOG.debug(f"Actual labels: {labels}")
assert (
input_ids == expected_input_ids
), f"Input IDs mismatch: {input_ids} != {expected_input_ids}"
assert (
labels == expected_labels
), f"Labels mismatch: {labels} != {expected_labels}"
class TestAssistantToolCallingChatTemplateLlama32Vision:
"""
Test class for assistant style datasets with tool_calling prompts using the llama-32_vision chat template.
"""
def test_llama32vision_train_on_assistant(
self, llama3_tokenizer, toolcalling_dataset, llama3_2_vision_chat_template_jinja
):
LOG.info(
"Testing assistant style datasets with tool_calling with llama-32 chat template, training on assistant"
)
strategy = ChatTemplateStrategy(
ChatTemplatePrompter(
llama3_tokenizer,
chat_template=get_chat_template(
"jinja", jinja_template=llama3_2_vision_chat_template_jinja
),
message_field_role="role",
message_field_content="content",
),
tokenizer=llama3_tokenizer,
train_on_inputs=False,
train_on_eos="turn",
sequence_len=512,
roles_to_train=["assistant"],
)
res = strategy.tokenize_prompt(toolcalling_dataset[0])
input_ids = res["input_ids"]
labels = res["labels"]
# fmt: off
expected_input_ids = [
128000, # bos
128006, 9125, 128007, 271, # system header
38766, 1303, 33025, 2696, 25, 6790, 220, 2366, 18, 198, 15724, 2696, 25, 220, 1114, 3799, 220, 2366, 19, 271, # system date prompt
2675, 527, 264, 11164, 430, 31680, 311, 9282, 20126, 13, 1472, 1288, 10052, 449, 279, 5089, 1511, 304, 279, 79002, 3813, 13, 128009, # system message
128006, 882, 128007, 271, # user header
19182, 11, 1148, 596, 279, 9499, 304, 12366, 1314, 1457, 30, 128009, # user message
128006, 78191, 128007, 271, # assistant header
5018, 609, 794, 330, 456, 11327, 54625, 498, 330, 14105, 794, 5324, 2588, 794, 330, 60704, 11, 9822, 498, 330, 3928, 794, 330, 66, 41347, 32075, 128009, # assistant message
128006, 23799, 4690, 128007, 271, # tool header
1, 1313, 13, 15, 1, 128009, # tool message
128006, 78191, 128007, 271, # assistant header
791, 9499, 304, 12366, 374, 220, 1313, 13, 15, 12628, 62447, 13, 128009 # assistant message
]
expected_labels = [
IGNORE_TOKEN_ID, # bos
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # system header
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # system date prompt
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # system message
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # user header
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # user message
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # assistant header
5018, 609, 794, 330, 456, 11327, 54625, 498, 330, 14105, 794, 5324, 2588, 794, 330, 60704, 11, 9822, 498, 330, 3928, 794, 330, 66, 41347, 32075, 128009, # assistant message
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # tool header
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # tool message
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # assistant header
791, 9499, 304, 12366, 374, 220, 1313, 13, 15, 12628, 62447, 13, 128009 # assistant message
]
# fmt: on
assert (
input_ids == expected_input_ids
), f"Input IDs mismatch: {input_ids} != {expected_input_ids}"
assert (
labels == expected_labels
), f"Labels mismatch: {labels} != {expected_labels}"
def test_llama32vision_train_on_tools(
self, llama3_tokenizer, toolcalling_dataset, llama3_2_vision_chat_template_jinja
):
LOG.info(
"Testing assistant style datasets with tool_calling with llama-32 chat template, training on tools"
)
# pylint: disable=duplicate-code
strategy = ChatTemplateStrategy(
ChatTemplatePrompter(
llama3_tokenizer,
chat_template=get_chat_template(
"jinja", jinja_template=llama3_2_vision_chat_template_jinja
),
message_field_role="role",
message_field_content="content",
),
tokenizer=llama3_tokenizer,
train_on_inputs=False,
train_on_eos="turn",
sequence_len=512,
roles_to_train=["assistant", "tool"],
)
res = strategy.tokenize_prompt(toolcalling_dataset[0])
input_ids = res["input_ids"]
labels = res["labels"]
# fmt: off
expected_input_ids = [
128000, # bos
128006, 9125, 128007, 271, # system header
38766, 1303, 33025, 2696, 25, 6790, 220, 2366, 18, 198, 15724, 2696, 25, 220, 1114, 3799, 220, 2366, 19, 271, # system date prompt
2675, 527, 264, 11164, 430, 31680, 311, 9282, 20126, 13, 1472, 1288, 10052, 449, 279, 5089, 1511, 304, 279, 79002, 3813, 13, 128009, # system message
128006, 882, 128007, 271, # user header
19182, 11, 1148, 596, 279, 9499, 304, 12366, 1314, 1457, 30, 128009, # user message
128006, 78191, 128007, 271, # assistant header
5018, 609, 794, 330, 456, 11327, 54625, 498, 330, 14105, 794, 5324, 2588, 794, 330, 60704, 11, 9822, 498, 330, 3928, 794, 330, 66, 41347, 32075, 128009, # assistant message
128006, 23799, 4690, 128007, 271, # tool header
1, 1313, 13, 15, 1, 128009, # tool message
128006, 78191, 128007, 271, # assistant header
791, 9499, 304, 12366, 374, 220, 1313, 13, 15, 12628, 62447, 13, 128009 # assistant message
]
expected_labels = [
IGNORE_TOKEN_ID, # bos
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # system header
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # system date prompt
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # system message
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # user header
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # user message
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # assistant header
5018, 609, 794, 330, 456, 11327, 54625, 498, 330, 14105, 794, 5324, 2588, 794, 330, 60704, 11, 9822, 498, 330, 3928, 794, 330, 66, 41347, 32075, 128009, # assistant message
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # tool header
IGNORE_TOKEN_ID, 1313, 13, 15, IGNORE_TOKEN_ID, 128009, # tool message
IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, IGNORE_TOKEN_ID, # assistant header
791, 9499, 304, 12366, 374, 220, 1313, 13, 15, 12628, 62447, 13, 128009 # assistant message
]
# fmt: on
assert (
input_ids == expected_input_ids
), f"Input IDs mismatch: {input_ids} != {expected_input_ids}"
assert (
labels == expected_labels
), f"Labels mismatch: {labels} != {expected_labels}"
if __name__ == "__main__":
unittest.main()
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