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# Conflicts: # vllm/hpu/ops.py
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from huggingface_hub import snapshot_download | ||
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from vllm import LLM, SamplingParams | ||
from vllm.lora.request import LoRARequest | ||
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sql_lora_path = snapshot_download(repo_id="yard1/llama-2-7b-sql-lora-test") | ||
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llm = LLM(model="meta-llama/Llama-2-7b-hf", | ||
enable_lora=True, | ||
max_num_seqs=2, | ||
dtype='bfloat16') | ||
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sampling_params = SamplingParams(temperature=0, | ||
max_tokens=1024, | ||
stop=["[/assistant]"]) | ||
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prompts = [ | ||
"[user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_74 (icao VARCHAR, airport VARCHAR)\n\n question: Name the ICAO for lilongwe international airport [/user] [assistant]", # noqa: E501 | ||
"[user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_11 (nationality VARCHAR, elector VARCHAR)\n\n question: When Anchero Pantaleone was the elector what is under nationality? [/user] [assistant]", # noqa: E501 | ||
"[user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_95 (one_mora VARCHAR, gloss VARCHAR, accented_mora VARCHAR)\n\n question: What is the one mora for a low tone mora with a gloss of /˩okiru/ [òkìɽɯ́]? [/user] [assistant]", # noqa: E501 | ||
"[user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE candidate (people_id VARCHAR, unsure_rate INTEGER); CREATE TABLE people (sex VARCHAR, people_id VARCHAR)\n\n question: which gender got the highest average uncertain ratio. [/user] [assistant]", # noqa: E501 | ||
"[user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_60 (pick INTEGER, former_wnba_team VARCHAR)\n\n question: What pick was a player that previously played for the Minnesota Lynx? [/user] [assistant]", # noqa: E501 | ||
"[user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_28138035_4 (womens_doubles VARCHAR, mens_singles VARCHAR)\n\n question: Name the women's doubles for werner schlager [/user] [assistant]" # noqa: E501 | ||
] | ||
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expected_output = [ | ||
" SELECT icao FROM table_name_74 WHERE airport = 'lilongwe international airport' ", # noqa: E501 | ||
" SELECT nationality FROM table_name_11 WHERE elector = 'Anchero Pantaleone' ", # noqa: E501 | ||
" SELECT one_mora FROM table_name_95 WHERE gloss = 'low tone mora with a gloss of /˩okiru/' [òkìɽɯ́] AND accented_mora = 'low tone mora with a gloss of /˩okiru/' [òkìɽɯ́] ", # noqa: E501 | ||
" SELECT sex FROM people WHERE people_id IN (SELECT people_id FROM candidate GROUP BY sex ORDER BY COUNT(people_id) DESC LIMIT 1) ", # noqa: E501 | ||
" SELECT pick FROM table_name_60 WHERE former_wnba_team = 'Minnesota Lynx' ", # noqa: E501 | ||
" SELECT womens_doubles FROM table_28138035_4 WHERE mens_singles = 'Werner Schlager' " # noqa: E501 | ||
] | ||
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outputs = llm.generate(prompts, | ||
sampling_params, | ||
lora_request=LoRARequest("sql_adapter", 1, | ||
sql_lora_path)) | ||
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for i, output in enumerate(outputs): | ||
prompt = output.prompt | ||
generated_text = output.outputs[0].text | ||
match = expected_output[i] == generated_text | ||
if not match: | ||
print( | ||
f"Comparison failed for request_id::{i}\n\t[PROMPT]{prompt!r}\n\t[GENERATED]{generated_text!r}\n\t[EXPECTED]{expected_output[i]!r}" # noqa: E501 | ||
) |
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from multiprocessing import Process | ||
from typing import List | ||
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from conftest import cleanup | ||
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import vllm | ||
from vllm.lora.request import LoRARequest | ||
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MODEL_PATH = "meta-llama/Llama-2-7b-hf" | ||
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def do_sample(llm: vllm.LLM, lora_path: str, lora_id: int) -> List[str]: | ||
prompts = [ | ||
"[user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_74 (icao VARCHAR, airport VARCHAR)\n\n question: Name the ICAO for lilongwe international airport [/user] [assistant]", # noqa: E501 | ||
"[user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_11 (nationality VARCHAR, elector VARCHAR)\n\n question: When Anchero Pantaleone was the elector what is under nationality? [/user] [assistant]", # noqa: E501 | ||
"[user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_95 (one_mora VARCHAR, gloss VARCHAR, accented_mora VARCHAR)\n\n question: What is the one mora for a low tone mora with a gloss of /˩okiru/ [òkìɽɯ́]? [/user] [assistant]", # noqa: E501 | ||
"[user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE candidate (people_id VARCHAR, unsure_rate INTEGER); CREATE TABLE people (sex VARCHAR, people_id VARCHAR)\n\n question: which gender got the highest average uncertain ratio. [/user] [assistant]", # noqa: E501 | ||
"[user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_60 (pick INTEGER, former_wnba_team VARCHAR)\n\n question: What pick was a player that previously played for the Minnesota Lynx? [/user] [assistant]", # noqa: E501 | ||
"[user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_28138035_4 (womens_doubles VARCHAR, mens_singles VARCHAR)\n\n question: Name the women's doubles for werner schlager [/user] [assistant]" # noqa: E501 | ||
] | ||
sampling_params = vllm.SamplingParams(temperature=0, | ||
max_tokens=256, | ||
stop=["[/assistant]"]) | ||
outputs = llm.generate( | ||
prompts, | ||
sampling_params, | ||
lora_request=LoRARequest(str(lora_id), lora_id, lora_path) | ||
if lora_id else None) | ||
# Print the outputs. | ||
generated_texts: List[str] = [] | ||
for output in outputs: | ||
prompt = output.prompt | ||
generated_text = output.outputs[0].text | ||
generated_texts.append(generated_text) | ||
print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}") | ||
return generated_texts | ||
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def _test_llama_lora(sql_lora_files, tp_size): | ||
llm = vllm.LLM(MODEL_PATH, | ||
enable_lora=True, | ||
max_num_seqs=16, | ||
max_loras=4, | ||
dtype='float32', | ||
tensor_parallel_size=tp_size) | ||
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expected_no_lora_output = [ | ||
"\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_75 (icao VARCHAR, airport VARCHAR)\n\n question: Name the ICAO for lilongwe international airport [/user] [assistant]\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_76 (icao VARCHAR, airport VARCHAR)\n\n question: Name the ICAO for lilongwe international airport [/user] [assistant]\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_77 (icao VARCHAR, airport VARCHAR)\n\n question: Name the ICAO for lilongwe international airport [/user] [assistant]\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_78 (icao VARCHAR, airport VARCHAR)\n\n question: Name the ICAO for lilongwe international airport [/user]", # noqa: E501 | ||
" Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_11 (nationality VARCHAR, elector VARCHAR)\n\n question: When Anchero Pantaleone was the elector what is under nationality? ", # noqa: E501 | ||
"\n\n answer: 1\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_96 (one_mora VARCHAR, gloss VARCHAR, accented_mora VARCHAR)\n\n question: What is the one mora for a high tone mora with a gloss of /˧kot/ [kòt]? [/user] [assistant]\n\n answer: 2\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_97 (one_mora VARCHAR, gloss VARCHAR, accented_mora VARCHAR)\n\n question: What is the one mora for a high tone mora with a gloss of /˧kot/ [kòt]? [/user] [assistant]\n\n answer: 2\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_98 (one_mora VARCHAR, gloss VARCHAR, accented_mora VARCHAR)\n\n question: What is the one m", # noqa: E501 | ||
" Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE candidate (people_id VARCHAR, unsure_rate INTEGER); CREATE TABLE people (sex VARCHAR, people_id VARCHAR)\n\n question: which gender got the highest average uncertain ratio. ", # noqa: E501 | ||
" Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_name_60 (pick INTEGER, former_wnba_team VARCHAR)\n\n question: What pick was a player that previously played for the Minnesota Lynx? ", # noqa: E501 | ||
"\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_28138035_4 (womens_doubles VARCHAR, mens_singles VARCHAR)\n\n question: Name the women's doubles for werner schlager [/user] [assistant]\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_28138035_4 (womens_doubles VARCHAR, mens_singles VARCHAR)\n\n question: Name the women's doubles for werner schlager [/user] [assistant]\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE table_28138035_4 (womens_doubles VARCHAR, mens_singles VARCHAR)\n\n question: Name the women's doubles for werner schlager [/user] [assistant]\n\n [user] Write a SQL query to answer the question based on the table schema.\n\n context: CREATE TABLE", # noqa: E501 | ||
] | ||
expected_lora_output = [ | ||
" SELECT icao FROM table_name_74 WHERE airport = 'lilongwe international airport' ", # noqa: E501 | ||
" SELECT nationality FROM table_name_11 WHERE elector = 'anchero pantaleone' ", # noqa: E501 | ||
" SELECT one_mora FROM table_name_95 WHERE gloss = 'low tone mora with a gloss of /˩okiru/' [òkìɽɯ́] AND accented_mora = 'low tone mora with a gloss of /˩okiru/' [òkìɽɯ́] ", # noqa: E501 | ||
" SELECT sex FROM people WHERE people_id IN (SELECT people_id FROM candidate GROUP BY sex ORDER BY COUNT(people_id) DESC LIMIT 1) ", # noqa: E501 | ||
" SELECT pick FROM table_name_60 WHERE former_wnba_team = 'Minnesota Lynx' ", # noqa: E501 | ||
" SELECT womens_doubles FROM table_28138035_4 WHERE mens_singles = 'Werner Schlager' " # noqa: E501 | ||
] | ||
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print("lora adapter created") | ||
assert do_sample(llm, sql_lora_files, lora_id=0) == expected_no_lora_output | ||
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print("lora 1") | ||
assert do_sample(llm, sql_lora_files, lora_id=1) == expected_lora_output | ||
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print("no lora") | ||
assert do_sample(llm, sql_lora_files, lora_id=0) == expected_no_lora_output | ||
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print("lora 2") | ||
assert do_sample(llm, sql_lora_files, lora_id=2) == expected_lora_output | ||
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print("removing lora") | ||
cleanup() | ||
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def test_llama_lora_1x(sql_lora_files): | ||
p = Process(target=_test_llama_lora, args=(sql_lora_files, 1)) | ||
p.start() | ||
p.join() | ||
assert p.exitcode == 0 | ||
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def test_llama_lora_2x(sql_lora_files): | ||
# Work-around to resolve stalling issue in multi-card scenario | ||
p = Process(target=_test_llama_lora, args=(sql_lora_files, 2)) | ||
p.start() | ||
p.join() | ||
assert p.exitcode == 0 | ||
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def test_llama_lora_4x(sql_lora_files): | ||
# Work-around to resolve stalling issue in multi-card scenario | ||
p = Process(target=_test_llama_lora, args=(sql_lora_files, 4)) | ||
p.start() | ||
p.join() | ||
assert p.exitcode == 0 |
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