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[Refactor] refactor prompt viewer & output reference #327

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[Refactor] refactor prompt viewer & output reference #327

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142 changes: 68 additions & 74 deletions tools/prompt_viewer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,8 +4,7 @@

from mmengine.config import Config, ConfigDict

from opencompass.openicl.icl_inferencer import (CLPInferencer, GenInferencer,
PPLInferencer)
from opencompass.openicl.icl_inferencer import GenInferencer, PPLInferencer
from opencompass.registry import ICL_PROMPT_TEMPLATES, ICL_RETRIEVERS
from opencompass.utils import (Menu, build_dataset_from_cfg,
build_model_from_cfg, dataset_abbr_from_cfg,
Expand Down Expand Up @@ -45,6 +44,24 @@ def parse_dataset_cfg(dataset_cfg: ConfigDict) -> Dict[str, ConfigDict]:
return dataset2cfg


def get_prompt(ice_idx, prompt_func, max_seq_len, model):
prompt = prompt_func(ice_idx)
num_token = model.get_token_len_from_template(prompt)
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Doesn't work when no model is provided

if max_seq_len is None:
print(f'Number of tokens: {num_token}')
return ice_idx, prompt
while len(ice_idx) > 0 and num_token > max_seq_len:
num_ice = len(ice_idx)
old_num_token = num_token
ice_idx = ice_idx[:-1]
prompt = prompt_func(ice_idx)
num_token = model.get_token_len_from_template(prompt)
print(f'Truncating ice {num_ice} -> {num_ice - 1}',
f'Number of tokens: {old_num_token} -> {num_token}')
print(f'Number of tokens: {num_token}')
return prompt


def print_prompts(model_cfg, dataset_cfg, count=1):
# TODO: A really dirty method that copies code from PPLInferencer and
# GenInferencer. In the future, the prompt extraction code should be
Expand Down Expand Up @@ -84,92 +101,70 @@ def print_prompts(model_cfg, dataset_cfg, count=1):
assert infer_cfg.inferencer.type in [PPLInferencer, GenInferencer], \
'Only PPLInferencer and GenInferencer are supported'

ice = retriever.generate_ice(ice_idx_list[0], ice_template=ice_template)
print('=' * 100)
print('Full in-context example:')
print('-' * 100)
print(ice)
print('=' * 100)
for idx in range(min(count, len(ice_idx_list))):
print('=' * 100)
print(f'Data Item #{idx}:')
if infer_cfg.inferencer.type == PPLInferencer:
labels = retriever.get_labels(ice_template=ice_template,
prompt_template=prompt_template)
ice = [
retriever.generate_ice(ice_idx_list[_idx],
ice_template=ice_template)
for _idx in range(len(ice_idx_list))
]
print('-' * 100)
print('ICE Template:')
print('-' * 100)
print(ice[0])
print('-' * 100)
for label in labels:
prompt = retriever.generate_label_prompt(
idx,
ice[idx],
label,
ice_template=ice_template,
prompt_template=prompt_template,
remain_sep=None)
if max_seq_len is not None:
prompt_token_num = model.get_token_len_from_template(
prompt)
while len(ice_idx_list[idx]
) > 0 and prompt_token_num > max_seq_len:
num_ice = len(ice_idx_list[idx])
print(f'Truncating ice {num_ice} -> {num_ice - 1}',
f'Number of tokens: {prompt_token_num} -> ...')
ice_idx_list[idx] = ice_idx_list[idx][:-1]
ice[idx] = retriever.generate_ice(
ice_idx_list[idx], ice_template=ice_template)
prompt = retriever.generate_label_prompt(
idx,
ice[idx],
label,
ice_template=ice_template,
prompt_template=prompt_template)
prompt_token_num = model.get_token_len_from_template(
prompt)
print(f'Number of tokens: {prompt_token_num}')
if model is not None:
prompt = model.parse_template(prompt, mode='ppl')
print('-' * 100)
print(f'Label: {label}')
print('Sample prompt:')
print('-' * 100)
print(prompt)
print('-' * 100)
elif infer_cfg.inferencer.type in [GenInferencer, CLPInferencer]:
ice_idx = ice_idx_list[idx]
ice = retriever.generate_ice(ice_idx, ice_template=ice_template)
prompt = retriever.generate_prompt_for_generate_task(
idx,
ice,
gen_field_replace_token=infer_cfg.inferencer.get(
'gen_field_replace_token', ''),
ice_template=ice_template,
prompt_template=prompt_template)
if max_seq_len is not None:
prompt_token_num = model.get_token_len_from_template(prompt)
while len(ice_idx) > 0 and prompt_token_num > max_seq_len:
num_ice = len(ice_idx)
print(f'Truncating ice {num_ice} -> {num_ice - 1}',
f'Number of tokens: {prompt_token_num} -> ...')
ice_idx = ice_idx[:-1]

def prompt_func(ice_idx):
ice = retriever.generate_ice(ice_idx,
ice_template=ice_template)
prompt = retriever.generate_prompt_for_generate_task(
return retriever.generate_label_prompt(
idx,
ice,
gen_field_replace_token=infer_cfg.inferencer.get(
'gen_field_replace_token', ''),
label,
ice_template=ice_template,
prompt_template=prompt_template)
prompt_token_num = model.get_token_len_from_template(
prompt)
print(f'Number of tokens: {prompt_token_num}')
prompt_template=prompt_template,
remain_sep=None)

print('-' * 100)
print(f'Label: {label}')
prompt = get_prompt(ice_idx_list[idx], prompt_func,
max_seq_len, model)
if model is not None:
prompt = model.parse_template(prompt, mode='ppl')
print('Prompt:')
print('-' * 61)
print(prompt)
print('-' * 100)
elif infer_cfg.inferencer.type == GenInferencer:

def prompt_func(ice_idx):
ice = retriever.generate_ice(ice_idx,
ice_template=ice_template)
return retriever.generate_prompt_for_generate_task(
idx,
ice,
gen_field_replace_token=infer_cfg.inferencer.get(
'gen_field_replace_token', ''),
ice_template=ice_template,
prompt_template=prompt_template)

prompt = get_prompt(ice_idx_list[idx], prompt_func, max_seq_len,
model)
if model is not None:
prompt = model.parse_template(prompt, mode='gen')
print('-' * 100)
print('Sample prompt:')
print('-' * 100)
print('Prompt:')
print('-' * 61)
print(prompt)
print('-' * 100)
else:
raise NotImplementedError

reference = dataset.test[idx][dataset.reader.output_column]
print('Reference:')
print('-' * 61)
print(reference)


def main():
Expand Down Expand Up @@ -215,7 +210,6 @@ def main():
print('=' * 64, '[BEGIN]', '=' * 64)
print(f'[MODEL]: {model_abbr}')
print(f'[DATASET]: {dataset_abbr}')
print('---')
print_prompts(model_cfg, dataset_cfg, args.count)
print('=' * 65, '[END]', '=' * 65)
print()
Expand Down