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https://github.com/ggerganov/llama.cpp.git
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Server: add tests for batch size, different seeds (#6950)
This commit is contained in:
Johannes Gäßler
GitHub
parent
1613ef8d8e
commit
3ea0d36000
@ -7,44 +7,16 @@ Feature: Results
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And a model file tinyllamas/split/stories15M-00001-of-00003.gguf from HF repo ggml-org/models
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And a model file test-model-00001-of-00003.gguf
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And 128 as batch size
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And 256 KV cache size
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And 1024 KV cache size
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And 128 max tokens to predict
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Scenario Outline: Multi users completion
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Given <n_slots> slots
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And continuous batching
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Scenario Outline: consistent results with same seed
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Given <n_slots> slots
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Then the server is starting
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Then the server is healthy
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Given 42 as seed
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And a prompt:
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"""
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Write a very long story about AI.
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"""
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Given 42 as seed
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And a prompt:
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"""
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Write a very long story about AI.
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"""
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Given 42 as seed
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And a prompt:
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"""
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Write a very long story about AI.
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"""
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Given 42 as seed
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And a prompt:
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"""
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Write a very long story about AI.
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"""
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Given 42 as seed
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And a prompt:
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"""
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Write a very long story about AI.
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"""
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Given 4 prompts "Title: Little Red Riding Hood But In Space\n\nSummary:" with seed 42
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Given concurrent completion requests
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Then the server is busy
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@ -55,3 +27,55 @@ Feature: Results
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| n_slots |
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| 1 |
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| 2 |
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Scenario Outline: different results with different seed
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Given <n_slots> slots
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Then the server is starting
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Then the server is healthy
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Given 1 prompts "Title: Little Red Riding Hood But In Space\n\nSummary:" with seed 42
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Given 1 prompts "Title: Little Red Riding Hood But In Space\n\nSummary:" with seed 43
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Given 1 prompts "Title: Little Red Riding Hood But In Space\n\nSummary:" with seed 44
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Given 1 prompts "Title: Little Red Riding Hood But In Space\n\nSummary:" with seed 45
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Given concurrent completion requests
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Then the server is busy
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Then the server is idle
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And all slots are idle
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Then all predictions are different
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Examples:
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| n_slots |
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| 1 |
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| 2 |
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Scenario Outline: consistent results with same seed and varying batch size
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Given 4 slots
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And <temp> temperature
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# And 0 as draft
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Then the server is starting
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Then the server is healthy
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Given 1 prompts "Write a very long story about AI." with seed 42
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And concurrent completion requests
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# Then the server is busy # Not all slots will be utilized.
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Then the server is idle
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And all slots are idle
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Given <n_parallel> prompts "Write a very long story about AI." with seed 42
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And concurrent completion requests
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# Then the server is busy # Not all slots will be utilized.
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Then the server is idle
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And all slots are idle
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Then all predictions are equal
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Examples:
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| n_parallel | temp |
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| 1 | 0.0 |
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| 2 | 0.0 |
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| 4 | 0.0 |
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| 1 | 1.0 |
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# FIXME: These tests fail on master. The problem seems to be the unified KV cache.
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# See https://github.com/ggerganov/whisper.cpp/issues/1941#issuecomment-1986923227
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# and https://github.com/ggerganov/llama.cpp/pull/6122#discussion_r1531405574 .
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# | 2 | 1.0 |
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# | 4 | 1.0 |
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@ -65,6 +65,7 @@ def step_server_config(context, server_fqdn, server_port):
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context.server_seed = None
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context.user_api_key = None
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context.response_format = None
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context.temperature = None
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context.tasks_result = []
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context.concurrent_tasks = []
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@ -232,15 +233,17 @@ async def step_all_slots_status(context, expected_slot_status_string):
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@async_run_until_complete
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async def step_request_completion(context, api_error):
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expect_api_error = api_error == 'raised'
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seeds = await completions_seed(context, num_seeds=1)
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completion = await request_completion(context.prompts.pop(),
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seeds[0] if seeds is not None else seeds,
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context.base_url,
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debug=context.debug,
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n_predict=context.n_predict,
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cache_prompt=context.cache_prompt,
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id_slot=context.id_slot,
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seed=await completions_seed(context),
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expect_api_error=expect_api_error,
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user_api_key=context.user_api_key)
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user_api_key=context.user_api_key,
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temperature=context.temperature)
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context.tasks_result.append(completion)
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if context.debug:
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print(f"Completion response: {completion}")
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@ -269,6 +272,15 @@ async def step_predictions_equal(context):
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context.tasks_result = []
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@step('all predictions are different')
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@async_run_until_complete
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async def step_predictions_equal(context):
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n_completions = await gather_tasks_results(context)
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assert n_completions >= 2, "need at least 2 completions"
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assert_all_predictions_different(context.tasks_result)
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context.tasks_result = []
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@step('the completion is truncated')
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def step_assert_completion_truncated(context):
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step_assert_completion_truncated(context, '')
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@ -311,6 +323,11 @@ def step_response_format(context, response_format):
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context.response_format = json.loads(response_format)
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@step('{temperature:f} temperature')
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def step_temperature(context, temperature):
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context.temperature = temperature
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@step('streaming is {enable_streaming}')
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def step_streaming(context, enable_streaming):
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context.enable_streaming = enable_streaming == 'enabled'
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@ -353,7 +370,10 @@ def step_n_ubatch(context, n_ubatch):
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@step('{seed:d} as seed')
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def step_seed(context, seed):
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context.seed = seed
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if context.seed is None:
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context.seed = [seed]
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else:
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context.seed.append(seed)
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@step('a prefix prompt')
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@ -413,7 +433,9 @@ async def step_oai_chat_completions(context, api_error):
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if context.debug:
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print(f"Submitting OAI compatible completions request...")
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expect_api_error = api_error == 'raised'
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seeds = await completions_seed(context, num_seeds=1),
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completion = await oai_chat_completions(context.prompts.pop(),
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seeds[0] if seeds is not None else seeds,
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context.system_prompt,
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context.base_url,
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'/v1/chat',
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@ -429,8 +451,6 @@ async def step_oai_chat_completions(context, api_error):
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response_format=context.response_format
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if hasattr(context, 'response_format') else None,
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seed=await completions_seed(context),
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user_api_key=context.user_api_key
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if hasattr(context, 'user_api_key') else None,
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@ -457,20 +477,31 @@ def step_a_prompt_prompt(context, prompt):
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context.n_prompts = len(context.prompts)
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@step('{num_prompts:d} prompts {prompt} with seed {seed:d}')
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def step_many_prompts(context, num_prompts, prompt, seed):
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if context.seed is None:
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context.seed = []
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for _ in range(num_prompts):
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context.seed.append(seed)
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context.prompts.append(prompt)
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context.n_prompts = len(context.prompts)
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@step('concurrent completion requests')
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@async_run_until_complete()
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async def step_concurrent_completion_requests(context):
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await concurrent_requests(context,
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request_completion,
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# prompt is inserted automatically
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context.base_url,
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debug=context.debug,
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prompt_prefix=context.prompt_prefix,
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prompt_suffix=context.prompt_suffix,
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n_predict=context.n_predict if hasattr(context, 'n_predict') else None,
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seed=await completions_seed(context),
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user_api_key=context.user_api_key if hasattr(context,
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'user_api_key') else None)
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await concurrent_requests(
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context,
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request_completion,
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# prompt is inserted automatically
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context.base_url,
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debug=context.debug,
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prompt_prefix=context.prompt_prefix,
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prompt_suffix=context.prompt_suffix,
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n_predict=context.n_predict if hasattr(context, 'n_predict') else None,
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user_api_key=context.user_api_key if hasattr(context, 'user_api_key') else None,
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temperature=context.temperature,
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)
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@step('concurrent OAI completions requests')
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@ -490,7 +521,6 @@ async def step_oai_chat_completions(context):
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if hasattr(context, 'enable_streaming') else None,
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response_format=context.response_format
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if hasattr(context, 'response_format') else None,
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seed=await completions_seed(context),
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user_api_key=context.user_api_key
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if hasattr(context, 'user_api_key') else None)
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@ -512,10 +542,6 @@ async def step_oai_chat_completions(context):
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if hasattr(context, 'enable_streaming') else None,
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response_format=context.response_format
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if hasattr(context, 'response_format') else None,
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seed=context.seed
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if hasattr(context, 'seed') else
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context.server_seed
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if hasattr(context, 'server_seed') else None,
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user_api_key=context.user_api_key
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if hasattr(context, 'user_api_key') else None)
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@ -544,7 +570,7 @@ async def all_prompts_are_predicted(context, expected_predicted_n=None):
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@async_run_until_complete
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async def step_compute_embedding(context):
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context.n_prompts = 1
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context.embeddings = await request_embedding(context_text(context), base_url=context.base_url)
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context.embeddings = await request_embedding(context_text(context), None, base_url=context.base_url)
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@step('all embeddings are the same')
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@ -585,7 +611,7 @@ def step_assert_embeddings(context):
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@async_run_until_complete
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async def step_oai_compute_embeddings(context):
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context.n_prompts = 1
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context.embeddings = await request_oai_embeddings(context_text(context),
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context.embeddings = await request_oai_embeddings(context_text(context), None,
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base_url=context.base_url,
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user_api_key=context.user_api_key,
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model=context.model)
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@ -594,7 +620,7 @@ async def step_oai_compute_embeddings(context):
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@step('an OAI compatible embeddings computation request for multiple inputs')
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@async_run_until_complete
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async def step_oai_compute_embeddings_multiple_inputs(context):
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context.embeddings = await request_oai_embeddings(context.prompts,
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context.embeddings = await request_oai_embeddings(context.prompts, None,
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base_url=context.base_url,
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user_api_key=context.user_api_key,
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model=context.model)
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@ -740,8 +766,9 @@ async def concurrent_requests(context, f_completion, *args, **kwargs):
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if context.debug:
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print(f"starting {context.n_prompts} concurrent completion requests...")
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assert context.n_prompts > 0
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seeds = await completions_seed(context)
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for prompt_no in range(context.n_prompts):
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shifted_args = [context.prompts.pop(), *args]
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shifted_args = [context.prompts.pop(), seeds[prompt_no], *args]
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context.concurrent_tasks.append(asyncio.create_task(f_completion(*shifted_args, **kwargs)))
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await asyncio.sleep(0.1)
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@ -781,6 +808,7 @@ def step_server_responds_with_status_code(context, status_code):
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async def request_completion(prompt,
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seed,
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base_url,
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debug=False,
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prompt_prefix=None,
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@ -788,9 +816,9 @@ async def request_completion(prompt,
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n_predict=None,
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cache_prompt=False,
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id_slot=None,
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seed=None,
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expect_api_error=None,
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user_api_key=None):
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user_api_key=None,
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temperature=None):
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if debug:
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print(f"Sending completion request: {prompt}")
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origin = "my.super.domain"
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@ -811,7 +839,8 @@ async def request_completion(prompt,
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"n_predict": n_predict if n_predict is not None else -1,
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"cache_prompt": cache_prompt,
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"id_slot": id_slot,
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"seed": seed if seed is not None else 42
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"seed": seed if seed is not None else 42,
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"temperature": temperature if temperature is not None else "0.8f",
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},
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headers=headers,
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timeout=3600) as response:
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@ -824,6 +853,7 @@ async def request_completion(prompt,
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async def oai_chat_completions(user_prompt,
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seed,
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system_prompt,
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base_url,
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base_path,
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@ -833,7 +863,6 @@ async def oai_chat_completions(user_prompt,
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n_predict=None,
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enable_streaming=None,
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response_format=None,
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seed=None,
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user_api_key=None,
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expect_api_error=None):
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if debug:
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@ -952,7 +981,7 @@ async def oai_chat_completions(user_prompt,
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return completion_response
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async def request_embedding(content, base_url=None):
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async def request_embedding(content, seed, base_url=None):
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async with aiohttp.ClientSession() as session:
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async with session.post(f'{base_url}/embedding',
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json={
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@ -963,7 +992,7 @@ async def request_embedding(content, base_url=None):
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return [response_json['embedding']]
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async def request_oai_embeddings(input,
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async def request_oai_embeddings(input, seed,
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base_url=None, user_api_key=None,
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model=None, async_client=False):
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# openai client always expects an api_key
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@ -1036,21 +1065,31 @@ def assert_n_tokens_predicted(completion_response, expected_predicted_n=None, re
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f' {n_predicted} <> {expected_predicted_n}')
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def assert_all_predictions_equal(completion_responses):
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content_0 = completion_responses[0]['content']
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if 'DEBUG' in os.environ and os.environ['DEBUG'] == 'ON':
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print(f"content 0: {content_0}")
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for i, response_i in enumerate(completion_responses):
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content_i = response_i['content']
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print(f"content {i}: {content_i}")
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for i, response_i in enumerate(completion_responses):
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content_i = response_i['content']
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for j, response_j in enumerate(completion_responses):
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if i == j:
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continue
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content_j = response_j['content']
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assert content_i == content_j, "contents not equal"
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i = 1
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for response in completion_responses[1:]:
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content = response['content']
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if 'DEBUG' in os.environ and os.environ['DEBUG'] == 'ON':
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print(f"content {i}: {content}")
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assert content == content_0, "contents not equal"
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i += 1
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def assert_all_predictions_different(completion_responses):
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if 'DEBUG' in os.environ and os.environ['DEBUG'] == 'ON':
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for i, response_i in enumerate(completion_responses):
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content_i = response_i['content']
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print(f"content {i}: {content_i}")
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for i, response_i in enumerate(completion_responses):
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content_i = response_i['content']
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for j, response_j in enumerate(completion_responses):
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if i == j:
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continue
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content_j = response_j['content']
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assert content_i != content_j, "contents not different"
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async def gather_tasks_results(context):
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@ -1145,9 +1184,22 @@ def assert_slots_status(slots, expected_slots):
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f" = {expected[key]} != {slot[key]}")
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async def completions_seed(context):
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return context.seed if hasattr(context, 'seed') and context.seed is not None \
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else context.server_seed if hasattr(context, 'server_seed') else None
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async def completions_seed(context, num_seeds=None):
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if hasattr(context, "seed") and context.seed is not None:
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assert len(context.seed) == context.n_prompts
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if num_seeds is None:
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num_seeds = context.n_prompts
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assert num_seeds <= context.n_prompts
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seeds = context.seed[:num_seeds]
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context.seed = context.seed[num_seeds:] if num_seeds < context.n_prompts else None
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return seeds
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if hasattr(context, "server_seed") and context.server_seed is not None:
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if num_seeds is None:
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return [context.server_seed] * context.n_prompts
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else:
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return [context.server_seed] * num_seeds
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return None
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def context_text(context):
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