baalajimaestro/llama.cpp
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feat: Support SPM infill (#1492)

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* Support SPM infill

* typo--

* one less layer of parenthesis necessary

* new required internals

* manually add bos/eos if model requires it

* add bos even when unknown

This is identical behaviour to llama.cpp

I guess any model that doesn't use BOS is recent enough to have the add_bos_token metadata.

* don't add bos/eos on non-infill pre-tokenized prompt

* add tokenizer hack to remove leading space in suffix

* I keep forgetting metadata are strings

* check if bos exists

* add example

* add cls/sep instead of bos/eos for WPM vocab

* simplify

* color-code filtered suffix

---------

Co-authored-by: Andrei Betlen <abetlen@gmail.com>
This commit is contained in:
Sigbjørn Skjæret 2024-06-13 09:45:24 +02:00 committed by GitHub
parent e342161371
commit dbcf64cf07
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3 changed files with 91 additions and 31 deletions
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33
examples/high_level_api/high_level_api_infill.py Normal file
View file

@ -0,0 +1,33 @@
import argparse
from llama_cpp import Llama
parser = argparse.ArgumentParser()
parser.add_argument("-m", "--model", type=str, default="../models/7B/ggml-models.bin")
parser.add_argument("-p", "--prompt", type=str, default="def add(")
parser.add_argument("-s", "--suffix", type=str, default="\n return sum\n\n")
parser.add_argument("-i", "--spm-infill", action='store_true')
args = parser.parse_args()
llm = Llama(model_path=args.model, n_gpu_layers=-1, spm_infill=args.spm_infill)
output = llm.create_completion(
temperature = 0.0,
repeat_penalty = 1.0,
prompt = args.prompt,
suffix = args.suffix,
)
# Models sometimes repeat suffix in response, attempt to filter that
response = output["choices"][0]["text"]
response_stripped = response.rstrip()
unwanted_response_suffix = args.suffix.rstrip()
unwanted_response_length = len(unwanted_response_suffix)
filtered = False
if unwanted_response_suffix and response_stripped[-unwanted_response_length:] == unwanted_response_suffix:
response = response_stripped[:-unwanted_response_length]
filtered = True
print(f"Fill-in-Middle completion{' (filtered)' if filtered else ''}:\n\n{args.prompt}\033[32m{response}\033[{'33' if filtered else '0'}m{args.suffix}\033[0m")

8
llama_cpp/_internals.py
View file

@ -170,6 +170,14 @@ class _LlamaModel:
assert self.model is not None
return llama_cpp.llama_token_eot(self.model)
def add_bos_token(self) -> int:
assert self.model is not None
return llama_cpp.llama_add_bos_token(self.model)
def add_eos_token(self) -> int:
assert self.model is not None
return llama_cpp.llama_add_eos_token(self.model)
# Tokenization
def tokenize(self, text: bytes, add_bos: bool, special: bool):

81
llama_cpp/llama.py
View file

@ -115,6 +115,7 @@ class Llama:
type_k: Optional[int] = None,
type_v: Optional[int] = None,
# Misc
spm_infill: bool = False,
verbose: bool = True,
# Extra Params
**kwargs, # type: ignore
@ -185,6 +186,7 @@ class Llama:
verbose: Print verbose output to stderr.
type_k: KV cache data type for K (default: f16)
type_v: KV cache data type for V (default: f16)
spm_infill: Use Suffix/Prefix/Middle pattern for infill (instead of Prefix/Suffix/Middle) as some models prefer this.
Raises:
ValueError: If the model path does not exist.
@ -343,6 +345,8 @@ class Llama:
self.lora_scale = lora_scale
self.lora_path = lora_path
self.spm_infill = spm_infill
if not os.path.exists(model_path):
raise ValueError(f"Model path does not exist: {model_path}")
@ -972,14 +976,33 @@ class Llama:
completion_id: str = f"cmpl-{str(uuid.uuid4())}"
created: int = int(time.time())
bos_token_id: int = self.token_bos()
cls_token_id: int = self._model.token_cls()
sep_token_id: int = self._model.token_sep()
prefix_token_id: int = self._model.token_prefix()
middle_token_id: int = self._model.token_middle()
suffix_token_id: int = self._model.token_suffix()
add_space_prefix: bool = self.metadata.get("tokenizer.ggml.add_space_prefix", "true") == "true"
bos_tokens: List[int] = [cls_token_id if cls_token_id != -1 else bos_token_id]
eos_tokens: List[int] = [sep_token_id if sep_token_id != -1 else self.token_eos()]
if (isinstance(prompt, list) and suffix is None) or self._model.add_bos_token() == 0 or bos_tokens[:1] == [-1]:
bos_tokens = []
if (isinstance(prompt, list) and suffix is None) or (self._model.add_eos_token() != 1 and sep_token_id == -1):
eos_tokens = []
suffix_space_prefix: int = 0
# Tokenizer hack to remove leading space
if add_space_prefix and suffix_token_id >= 0 and suffix:
suffix = "☺" + suffix
suffix_space_prefix = 2
# If prompt is empty, initialize completion with BOS token to avoid
# detokenization including a space at the beginning of the completion
completion_tokens: List[int] = [] if len(prompt) > 0 else [self.token_bos()]
completion_tokens: List[int] = [] if len(prompt) > 0 else [bos_token_id]
# Add blank space to start of prompt to match OG llama tokenizer
prompt_tokens: List[int] = (
prefix_tokens: List[int] = (
(
[prefix_token_id]
if prefix_token_id >= 0 and suffix is not None
@ -988,38 +1011,33 @@ class Llama:
+
(
(
self.tokenize(prompt.encode("utf-8"), add_bos=(prefix_token_id < 0 or suffix is None), special=(prefix_token_id < 0 or suffix is None))
self.tokenize(prompt.encode("utf-8"), add_bos=False, special=(prefix_token_id < 0 or suffix is None))
if prompt != ""
else (
[]
if prefix_token_id >= 0 and suffix is not None
else [self.token_bos()]
)
else []
)
if isinstance(prompt, str)
else prompt
)
+
(
(
[suffix_token_id]
+
(
self.tokenize(suffix.encode("utf-8"), add_bos=False, special=False)
if suffix
else []
)
)
if suffix_token_id >= 0 and suffix is not None
else []
)
+
(
[middle_token_id]
if middle_token_id >= 0 and suffix is not None
else []
)
)
suffix_tokens: List[int] = (
(
[suffix_token_id]
+
(
self.tokenize(suffix.encode("utf-8"), add_bos=False, special=False)[suffix_space_prefix:]
if suffix
else []
)
)
if suffix_token_id >= 0 and suffix is not None
else []
)
middle_tokens: List[int] = (
[middle_token_id]
if middle_token_id >= 0 and suffix is not None
else []
)
prompt_tokens: List[int] = bos_tokens + ((suffix_tokens + prefix_tokens + middle_tokens) if self.spm_infill else (prefix_tokens + suffix_tokens + middle_tokens)) + eos_tokens
text: bytes = b""
returned_tokens: int = 0
stop = (
@ -1176,7 +1194,7 @@ class Llama:
# not sure how to handle this branch when dealing
# with CJK output, so keep it unchanged
for token in remaining_tokens:
if token == self.token_bos():
if token == bos_token_id:
continue
token_end_position += len(self.detokenize([token], prev_tokens=prompt_tokens + completion_tokens[:returned_tokens]))
# Check if stop sequence is in the token
@ -1303,7 +1321,7 @@ class Llama:
logprobs_or_none: Optional[CompletionLogprobs] = None
if logprobs is not None:
if token == self.token_bos():
if token == bos_token_id:
continue
token_str = self.detokenize([token]).decode(
"utf-8", errors="ignore"
@ -1431,7 +1449,7 @@ class Llama:
for idx, (token, token_str, logprobs_token) in enumerate(
zip(all_tokens, all_token_strs, all_logprobs)
):
if token == self.token_bos():
if token == bos_token_id:
continue
text_offsets.append(
text_offset
@ -1858,6 +1876,7 @@ class Llama:
type_k=self.context_params.type_k,
type_v=self.context_params.type_v,
# Misc
spm_infill=self.spm_infill,
verbose=self.verbose,
)