vllm/tests/models/utils.py
2024-08-29 19:19:08 -07:00

147 lines
5.9 KiB
Python

import warnings
from typing import Dict, List, Optional, Sequence, Tuple, Union
from vllm.sequence import Logprob, SampleLogprobs
TokensText = Tuple[List[int], str]
def check_outputs_equal(
*,
outputs_0_lst: Sequence[TokensText],
outputs_1_lst: Sequence[TokensText],
name_0: str,
name_1: str,
):
"""
Compare the two sequences generated by different models,
which should be equal.
"""
assert len(outputs_0_lst) == len(outputs_1_lst)
for prompt_idx, (outputs_0,
outputs_1) in enumerate(zip(outputs_0_lst,
outputs_1_lst)):
output_ids_0, output_str_0 = outputs_0
output_ids_1, output_str_1 = outputs_1
# The text and token outputs should exactly match
fail_msg = (f"Test{prompt_idx}:"
f"\n{name_0}:\t{output_str_0!r}"
f"\n{name_1}:\t{output_str_1!r}")
assert output_str_0 == output_str_1, fail_msg
assert output_ids_0 == output_ids_1, fail_msg
TokensTextLogprobs = Tuple[List[int], str, Optional[Union[List[Dict[int,
float]],
SampleLogprobs]]]
# Allow for tokens to be represented as str's rather than IDs
TextTextLogprobs = Tuple[List[str], str, Optional[Union[List[Dict[str, float]],
List[Dict[str,
Logprob]]]]]
def check_logprobs_close(
*,
outputs_0_lst: Sequence[Union[TokensTextLogprobs, TextTextLogprobs]],
outputs_1_lst: Sequence[Union[TokensTextLogprobs, TextTextLogprobs]],
name_0: str,
name_1: str,
num_outputs_0_skip_tokens: int = 0,
warn_on_mismatch: bool = True,
always_check_logprobs: bool = False,
) -> None:
"""Compare the logprobs of two sequences generated by different models,
which should be similar but not necessarily equal.
Args:
outputs_0_lst: First sequence to compare
outputs_0_lst: Second sequence to compare
name_0: sequence #0 name
name_1: sequence #1 name
num_outputs_0_skip_tokens: If > 0, specifies the number of initial
sequence #0 tokens & logprobs to discard
before comparison, i.e. all
of sequence #1 will be compared to
sequence #0 beginning at index
num_outputs_0_skip_tokens
warn_on_mismatch: Issue a warning if there is token-wise or text-wise
mismatch between the two sequences
always_check_logprobs: If true, check logprobs even when tokens match
"""
assert len(outputs_0_lst) == len(outputs_1_lst)
# Loop through responses to each prompt.
for prompt_idx, (outputs_0,
outputs_1) in enumerate(zip(outputs_0_lst,
outputs_1_lst)):
output_ids_0, output_str_0, logprobs_0 = outputs_0
output_ids_1, output_str_1, logprobs_1 = outputs_1
if logprobs_0 is None:
logprobs_0 = [None] * len(output_ids_0)
if logprobs_1 is None:
logprobs_1 = [None] * len(output_ids_1)
# Skip specified number of initial sequence #0 tokens
# & logprobs, leaving output text as-is for simplicity
# (text mismatches may generate warnings but do not
# cause the test to fail.)
if num_outputs_0_skip_tokens < 0:
raise ValueError("num_outputs_0_skip_tokens must be non-negative")
output_ids_0 = output_ids_0[num_outputs_0_skip_tokens:]
logprobs_0 = logprobs_0[num_outputs_0_skip_tokens:]
# Loop through generated tokens.
for idx, (output_id_0,
output_id_1) in enumerate(zip(output_ids_0, output_ids_1)):
is_tok_mismatch = output_id_0 != output_id_1
# If generated tokens don't match
# or it is desired to always check logprobs,
# then
if is_tok_mismatch or always_check_logprobs:
logprobs_elem_0 = logprobs_0[idx]
logprobs_elem_1 = logprobs_1[idx]
# Each predicted token must be in top N logprobs of the other
fail_msg = (
f"Test{prompt_idx}:"
f"\nMatched tokens:\t{output_ids_0[:idx]}"
f"\n{name_0}:\t{output_str_0!r}\t{logprobs_elem_0}"
f"\n{name_1}:\t{output_str_1!r}\t{logprobs_elem_1}")
assert logprobs_elem_0 is not None, fail_msg
assert logprobs_elem_1 is not None, fail_msg
assert output_id_0 in logprobs_elem_1, fail_msg
assert output_id_1 in logprobs_elem_0, fail_msg
if warn_on_mismatch and is_tok_mismatch:
with warnings.catch_warnings():
# This ensures that repeated warnings are shown
# in the output, not just the first occurrence
warnings.simplefilter("always")
warnings.warn(fail_msg, stacklevel=2)
# Break out since sequences will now diverge.
break
else:
if output_str_0 != output_str_1 and warn_on_mismatch:
# The token outputs exactly match,
# so the text outputs should exactly match as well
fail_msg = (f"Test{prompt_idx}:"
f"\n{name_0}:\t{output_str_0!r}"
f"\n{name_1}:\t{output_str_1!r}")
with warnings.catch_warnings():
# This ensures that repeated warnings are shown
# in the output, not just the first occurrence
warnings.simplefilter("always")
warnings.warn(fail_msg, stacklevel=2)