mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-26 14:20:31 +01:00
server : add --no-context-shift option (#9607)
* server : add --no-context-shift option * small fix * Update examples/server/tests/features/embeddings.feature Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * tests : minor fix * revert usage of GGML_ASSERT * update server documentation --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
Xuan Son Nguyen
GitHub
parent
f0c7b5edf8
commit
0b3bf966f4
@ -691,7 +691,7 @@ gpt_params_context gpt_params_parser_init(gpt_params & params, llama_example ex,
|
||||
[](gpt_params & params) {
|
||||
params.ctx_shift = false;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_MAIN}));
|
||||
).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SERVER}));
|
||||
add_opt(llama_arg(
|
||||
{"--chunks"}, "N",
|
||||
format("max number of chunks to process (default: %d, -1 = all)", params.n_chunks),
|
||||
|
||||
@ -21,8 +21,6 @@ The project is under active development, and we are [looking for feedback and co
|
||||
| -------- | ----------- |
|
||||
| `-h, --help, --usage` | print usage and exit |
|
||||
| `--version` | show version and build info |
|
||||
| `-v, --verbose` | print verbose information |
|
||||
| `--verbosity N` | set specific verbosity level (default: 0) |
|
||||
| `-t, --threads N` | number of threads to use during generation (default: -1)<br/>(env: LLAMA_ARG_THREADS) |
|
||||
| `-tb, --threads-batch N` | number of threads to use during batch and prompt processing (default: same as --threads) |
|
||||
| `-C, --cpu-mask M` | CPU affinity mask: arbitrarily long hex. Complements cpu-range (default: "") |
|
||||
@ -40,15 +38,18 @@ The project is under active development, and we are [looking for feedback and co
|
||||
| `-b, --batch-size N` | logical maximum batch size (default: 2048)<br/>(env: LLAMA_ARG_BATCH) |
|
||||
| `-ub, --ubatch-size N` | physical maximum batch size (default: 512)<br/>(env: LLAMA_ARG_UBATCH) |
|
||||
| `--keep N` | number of tokens to keep from the initial prompt (default: 0, -1 = all) |
|
||||
| `--no-context-shift` | disables context shift on inifinite text generation (default: disabled) |
|
||||
| `-fa, --flash-attn` | enable Flash Attention (default: disabled)<br/>(env: LLAMA_ARG_FLASH_ATTN) |
|
||||
| `-p, --prompt PROMPT` | prompt to start generation with |
|
||||
| `--no-perf` | disable internal libllama performance timings (default: false)<br/>(env: LLAMA_ARG_NO_PERF) |
|
||||
| `-f, --file FNAME` | a file containing the prompt (default: none) |
|
||||
| `-bf, --binary-file FNAME` | binary file containing the prompt (default: none) |
|
||||
| `-e, --escape` | process escapes sequences (\n, \r, \t, \', \", \\) (default: true) |
|
||||
| `--no-escape` | do not process escape sequences |
|
||||
| `-sp, --special` | special tokens output enabled (default: false) |
|
||||
| `--spm-infill` | use Suffix/Prefix/Middle pattern for infill (instead of Prefix/Suffix/Middle) as some models prefer this. (default: disabled) |
|
||||
| `--samplers SAMPLERS` | samplers that will be used for generation in the order, separated by ';'<br/>(default: top_k;tfs_z;typ_p;top_p;min_p;temperature) |
|
||||
| `-s, --seed SEED` | RNG seed (default: -1, use random seed for < 0) |
|
||||
| `-s, --seed SEED` | RNG seed (default: 4294967295, use random seed for 4294967295) |
|
||||
| `--sampling-seq SEQUENCE` | simplified sequence for samplers that will be used (default: kfypmt) |
|
||||
| `--ignore-eos` | ignore end of stream token and continue generating (implies --logit-bias EOS-inf) |
|
||||
| `--penalize-nl` | penalize newline tokens (default: false) |
|
||||
@ -87,7 +88,7 @@ The project is under active development, and we are [looking for feedback and co
|
||||
| `-ctk, --cache-type-k TYPE` | KV cache data type for K (default: f16) |
|
||||
| `-ctv, --cache-type-v TYPE` | KV cache data type for V (default: f16) |
|
||||
| `-dt, --defrag-thold N` | KV cache defragmentation threshold (default: -1.0, < 0 - disabled)<br/>(env: LLAMA_ARG_DEFRAG_THOLD) |
|
||||
| `-np, --parallel N` | number of parallel sequences to decode (default: 1)<br/>(env: LLAMA_ARG_N_PARALLEL) |
|
||||
| `-np, --parallel N` | number of parallel sequences to decode (default: 1)<br/>(env: LLAMA_ARG_N_PARALLEL) |
|
||||
| `-cb, --cont-batching` | enable continuous batching (a.k.a dynamic batching) (default: enabled)<br/>(env: LLAMA_ARG_CONT_BATCHING) |
|
||||
| `-nocb, --no-cont-batching` | disable continuous batching<br/>(env: LLAMA_ARG_NO_CONT_BATCHING) |
|
||||
| `--mlock` | force system to keep model in RAM rather than swapping or compressing |
|
||||
@ -128,12 +129,13 @@ The project is under active development, and we are [looking for feedback and co
|
||||
| `-sps, --slot-prompt-similarity SIMILARITY` | how much the prompt of a request must match the prompt of a slot in order to use that slot (default: 0.50, 0.0 = disabled)<br/> |
|
||||
| `--lora-init-without-apply` | load LoRA adapters without applying them (apply later via POST /lora-adapters) (default: disabled) |
|
||||
| `-ld, --logdir LOGDIR` | path under which to save YAML logs (no logging if unset) |
|
||||
| `--log-test` | Log test |
|
||||
| `--log-disable` | Log disable |
|
||||
| `--log-enable` | Log enable |
|
||||
| `--log-new` | Log new |
|
||||
| `--log-append` | Log append |
|
||||
| `--log-file FNAME` | Log file |
|
||||
| `--log-file FNAME` | Log to file |
|
||||
| `--log-colors` | Enable colored logging<br/>(env: LLAMA_LOG_COLORS) |
|
||||
| `-v, --verbose, --log-verbose` | Set verbosity level to infinity (i.e. log all messages, useful for debugging) |
|
||||
| `-lv, --verbosity, --log-verbosity N` | Set the verbosity threshold. Messages with a higher verbosity will be ignored.<br/>(env: LLAMA_LOG_VERBOSITY) |
|
||||
| `--log-prefix` | Enable prefx in log messages<br/>(env: LLAMA_LOG_PREFIX) |
|
||||
| `--log-timestamps` | Enable timestamps in log messages<br/>(env: LLAMA_LOG_TIMESTAMPS) |
|
||||
|
||||
Note: If both command line argument and environment variable are both set for the same param, the argument will take precedence over env var.
|
||||
|
||||
|
||||
@ -1180,6 +1180,15 @@ struct server_context {
|
||||
SLT_DBG(slot, "stopped by limit, n_decoded = %d, n_predict = %d\n", slot.n_decoded, slot.params.n_predict);
|
||||
}
|
||||
|
||||
// if context shift is disabled, we stop when it reaches the context limit
|
||||
if (slot.n_decoded >= slot.n_ctx) {
|
||||
slot.truncated = true;
|
||||
slot.stopped_limit = true;
|
||||
slot.has_next_token = false;
|
||||
|
||||
SLT_DBG(slot, "stopped due to running out of context capacity, n_decoded = %d, n_ctx = %d\n", slot.n_decoded, slot.n_ctx);
|
||||
}
|
||||
|
||||
if (llama_token_is_eog(model, result.tok)) {
|
||||
slot.stopped_eos = true;
|
||||
slot.has_next_token = false;
|
||||
@ -1480,7 +1489,7 @@ struct server_context {
|
||||
if (result.error) {
|
||||
error_handler(result.data);
|
||||
cancel_tasks(id_tasks);
|
||||
break;
|
||||
return;
|
||||
}
|
||||
|
||||
size_t idx = result.data["index"];
|
||||
@ -1827,6 +1836,14 @@ struct server_context {
|
||||
for (server_slot & slot : slots) {
|
||||
if (slot.ga_n == 1) {
|
||||
if (slot.is_processing() && (int) system_tokens.size() + slot.n_past >= slot.n_ctx - 1) {
|
||||
if (!params.ctx_shift) {
|
||||
// this check is redundant (for good)
|
||||
// we should never get here, because generation should already stopped in process_token()
|
||||
slot.release();
|
||||
send_error(slot, "context shift is disabled", ERROR_TYPE_SERVER);
|
||||
continue;
|
||||
}
|
||||
|
||||
// Shift context
|
||||
const int n_keep = slot.params.n_keep + add_bos_token;
|
||||
const int n_left = (int) system_tokens.size() + slot.n_past - n_keep;
|
||||
@ -1961,6 +1978,14 @@ struct server_context {
|
||||
continue;
|
||||
}
|
||||
} else {
|
||||
if (!params.ctx_shift) {
|
||||
// if context shift is disabled, we make sure prompt size is smaller than KV size
|
||||
if ((int) system_tokens.size() + slot.n_prompt_tokens >= slot.n_ctx) {
|
||||
slot.release();
|
||||
send_error(slot, "the request exceeds the available context size. try increasing the context size or enable context shift", ERROR_TYPE_INVALID_REQUEST);
|
||||
continue;
|
||||
}
|
||||
}
|
||||
if (slot.params.n_keep < 0) {
|
||||
slot.params.n_keep = slot.n_prompt_tokens;
|
||||
}
|
||||
|
||||
62
examples/server/tests/features/ctx_shift.feature
Normal file
62
examples/server/tests/features/ctx_shift.feature
Normal file
@ -0,0 +1,62 @@
|
||||
@llama.cpp
|
||||
@ctx_shift
|
||||
Feature: llama.cpp server
|
||||
|
||||
Background: Server startup
|
||||
Given a server listening on localhost:8080
|
||||
And a model file tinyllamas/stories260K.gguf from HF repo ggml-org/models
|
||||
And a model file test-model.gguf
|
||||
And a model alias tinyllama-2
|
||||
And BOS token is 1
|
||||
And 42 as server seed
|
||||
And 256 KV cache size
|
||||
And 32 as batch size
|
||||
And 2 slots
|
||||
|
||||
Scenario: Inference with context shift
|
||||
And 64 server max tokens to predict
|
||||
Then the server is starting
|
||||
Then the server is healthy
|
||||
Given a prompt:
|
||||
"""
|
||||
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
|
||||
Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
|
||||
Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.
|
||||
Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
|
||||
"""
|
||||
And a completion request with no api error
|
||||
Then 64 tokens are predicted matching fun|Annaks|popcorns|pictry|bowl
|
||||
And the completion is truncated
|
||||
And 109 prompt tokens are processed
|
||||
|
||||
Scenario Outline: Inference without context shift
|
||||
And <n_predict> server max tokens to predict
|
||||
And disable context shifting
|
||||
Then the server is starting
|
||||
Then the server is healthy
|
||||
Given a prompt:
|
||||
"""
|
||||
Hi how are you
|
||||
"""
|
||||
And a completion request with no api error
|
||||
Then <n_token_output> tokens are predicted matching twind|Anna
|
||||
And the completion is <truncated> truncated
|
||||
And 8 prompt tokens are processed
|
||||
Examples:
|
||||
| n_predict | n_token_output | truncated |
|
||||
| 64 | 64 | not |
|
||||
| -1 | 120 | |
|
||||
|
||||
Scenario: Inference without context shift (expected error: prompt too long)
|
||||
And disable context shifting
|
||||
Then the server is starting
|
||||
Then the server is healthy
|
||||
Given a prompt:
|
||||
"""
|
||||
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
|
||||
Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
|
||||
Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.
|
||||
Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
|
||||
"""
|
||||
And a completion request with 400 api error
|
||||
|
||||
@ -10,11 +10,11 @@ Feature: llama.cpp server
|
||||
And 42 as server seed
|
||||
And 2 slots
|
||||
# the bert-bge-small model has context size of 512
|
||||
# since the generated prompts are as big as the batch size, we need to set the batch size to 512
|
||||
# since the generated prompts are as big as the batch size, we need to set the batch size to <= 512
|
||||
# ref: https://huggingface.co/BAAI/bge-small-en-v1.5/blob/5c38ec7c405ec4b44b94cc5a9bb96e735b38267a/config.json#L20
|
||||
And 512 as batch size
|
||||
And 512 as ubatch size
|
||||
And 2048 KV cache size
|
||||
And 128 as batch size
|
||||
And 128 as ubatch size
|
||||
And 512 KV cache size
|
||||
And embeddings extraction
|
||||
Then the server is starting
|
||||
Then the server is healthy
|
||||
@ -26,6 +26,20 @@ Feature: llama.cpp server
|
||||
"""
|
||||
Then embeddings are generated
|
||||
|
||||
Scenario: Embedding (error: prompt too long)
|
||||
When embeddings are computed for:
|
||||
"""
|
||||
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
|
||||
Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
|
||||
Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.
|
||||
Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
|
||||
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
|
||||
Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
|
||||
Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.
|
||||
Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
|
||||
"""
|
||||
And embeddings request with 500 api error
|
||||
|
||||
Scenario: OAI Embeddings compatibility
|
||||
Given a model bert-bge-small
|
||||
When an OAI compatible embeddings computation request for:
|
||||
|
||||
@ -77,6 +77,7 @@ def step_server_config(context, server_fqdn: str, server_port: str):
|
||||
context.response_format = None
|
||||
context.temperature = None
|
||||
context.lora_file = None
|
||||
context.disable_ctx_shift = False
|
||||
|
||||
context.tasks_result = []
|
||||
context.concurrent_tasks = []
|
||||
@ -148,7 +149,7 @@ def step_n_slots(context, n_slots: int):
|
||||
|
||||
@step('{n_predict:d} server max tokens to predict')
|
||||
def step_server_n_predict(context, n_predict: int):
|
||||
context.n_server_predict = n_predict
|
||||
context.n_server_predict = n_predict if n_predict > 0 else None
|
||||
|
||||
|
||||
@step('{slot_save_path} as slot save path')
|
||||
@ -180,6 +181,9 @@ def step_server_embeddings(context):
|
||||
def step_server_metrics(context):
|
||||
context.server_metrics = True
|
||||
|
||||
@step('disable context shifting')
|
||||
def step_server_disable_ctx_shift(context):
|
||||
context.disable_ctx_shift = True
|
||||
|
||||
@step("the server is starting")
|
||||
def step_start_server(context):
|
||||
@ -257,7 +261,7 @@ async def step_all_slots_status(context, expected_slot_status_string: Literal['i
|
||||
@step('a completion request with {api_error} api error')
|
||||
@async_run_until_complete
|
||||
async def step_request_completion(context, api_error: Literal['raised'] | str):
|
||||
expect_api_error = api_error == 'raised'
|
||||
expect_api_error = api_error == 'raised' or api_error != 'no'
|
||||
seeds = await completions_seed(context, num_seeds=1)
|
||||
completion = await request_completion(context.prompts.pop(),
|
||||
seeds[0] if seeds is not None else seeds,
|
||||
@ -272,8 +276,11 @@ async def step_request_completion(context, api_error: Literal['raised'] | str):
|
||||
context.tasks_result.append(completion)
|
||||
if context.debug:
|
||||
print(f"Completion response: {completion}")
|
||||
if expect_api_error:
|
||||
if api_error == 'raised':
|
||||
assert completion == 401, f"completion must be an 401 status code: {completion}"
|
||||
elif api_error.isdigit():
|
||||
api_error_code = int(api_error)
|
||||
assert completion == api_error_code, f"completion must be an {api_error_code} status code: {completion}"
|
||||
|
||||
|
||||
@step('{predicted_n:d} tokens are predicted matching {re_content}')
|
||||
@ -645,6 +652,9 @@ def step_assert_embeddings(context):
|
||||
for embedding in context.embeddings:
|
||||
assert_embeddings(embedding)
|
||||
|
||||
@step('embeddings request with {api_error_code:d} api error')
|
||||
def step_assert_embeddings(context, api_error_code: int):
|
||||
assert context.embeddings == api_error_code, f"embeddings request must return code {api_error_code}, but got {context.embeddings}"
|
||||
|
||||
@step('an OAI compatible embeddings computation request for')
|
||||
@async_run_until_complete
|
||||
@ -1089,15 +1099,17 @@ async def oai_chat_completions(user_prompt,
|
||||
return completion_response
|
||||
|
||||
|
||||
async def request_embedding(content, seed, base_url=None) -> list[list[float]]:
|
||||
async def request_embedding(content, seed, base_url=None) -> list[list[float]] | int:
|
||||
async with aiohttp.ClientSession(timeout=DEFAULT_TIMEOUT_SECONDS) as session:
|
||||
async with session.post(f'{base_url}/embedding',
|
||||
json={
|
||||
"content": content,
|
||||
}) as response:
|
||||
assert response.status == 200
|
||||
response_json = await response.json()
|
||||
return [response_json['embedding']]
|
||||
if response.status == 200:
|
||||
response_json = await response.json()
|
||||
return [response_json['embedding']]
|
||||
else:
|
||||
return response.status
|
||||
|
||||
|
||||
async def request_oai_embeddings(input, seed,
|
||||
@ -1372,6 +1384,8 @@ def start_server_background(context):
|
||||
server_args.append('--verbose')
|
||||
if context.lora_file:
|
||||
server_args.extend(['--lora', context.lora_file])
|
||||
if context.disable_ctx_shift:
|
||||
server_args.extend(['--no-context-shift'])
|
||||
|
||||
args = [str(arg) for arg in [context.server_path, *server_args]]
|
||||
print(f"bench: starting server with: {' '.join(args)}")
|
||||
|
||||
Loading…
Reference in New Issue
Block a user