Logging and Sampling outlines.processors
#35
Draft
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
lapp0
force-pushed
the
logits-processor-integrations-fix
branch
2 times, most recently
from
c07de55
to
c3e8673
Compare
|
The idea is interesting. Do we really want to increase the surface area of the library? There's a risk of spreading ourselves too thinly by adding extra code to maintain. |
lapp0
force-pushed
the
logging-processor
branch
from
4d0b9bd
to
d49fd23
Compare
lapp0
changed the base branch from
logits-processor-integrations-fix
to
main
lapp0
force-pushed
the
logging-processor
branch
from
d49fd23
to
31a485a
Compare
lapp0
force-pushed
the
logging-processor
branch
from
31a485a
to
6e69272
Compare
cpfiffer
reviewed
Sep 9, 2024
There was a problem hiding this comment.
A few comments here and there. Was able to get this to work with a modified example:
import outlines
import outlines.processors as processors
model = outlines.models.transformers(
"openaccess-ai-collective/tiny-mistral",
)
# Create a chained logits processor
logits_processor = (
processors.sequence_logging(model.tokenizer) | # Log the generated sequence
processors.logits_logging(model.tokenizer) | # Log the raw logits
processors.regex(r"[0-9]*", model.tokenizer) | # Restrict the logits to match the pattern
processors.temperature(0.5) | # Set temperature to 0.5
processors.logits_logging(model.tokenizer) # Log the restricted, temperature-augmentent, sampled logits
)
generator = outlines.generate.base(model, logits_processor)
generator("What is your favorite number? ")We'll also need to export the base generator method, i.e. __init__.py should include this line:
from .api import SequenceGenerator
from .base import base
from .cfg import cfg
from .choice import choice
from .format import format
from .fsm import fsm
from .json import json
from .regex import regex
from .text import text| processors.logits_logging(model.tokenizer) # Log the restricted, temperature-augmentent, sampled logits | ||
| ) | ||
|
|
||
| generator = outlines.generate.base(model, logits_process) |
There was a problem hiding this comment.
Suggested change
| generator = outlines.generate.base(model, logits_process) | |
| generator = outlines.generate.text(model, logits_processor) |
- should be
logits_processor - Is
basedefined here? I haven't been able to find it (yet)
There was a problem hiding this comment.
Comment on lines
+30
to
+33
| model = outlines.models.llamacpp( | ||
| repo_id="M4-ai/TinyMistral-248M-v2-Instruct-GGUF", | ||
| filename="TinyMistral-248M-v2-Instruct.Q4_K_M.gguf" | ||
| ) |
There was a problem hiding this comment.
This doesn't seem to work with llamacpp, but it does work with transformers:
import outlines
import outlines.processors as processors
model = outlines.models.transformers(
"openaccess-ai-collective/tiny-mistral",
)
# Create a chained logits processor
logits_processor = (
processors.sequence_logging(model.tokenizer) | # Log the generated sequence
processors.logits_logging(model.tokenizer) | # Log the raw logits
processors.regex(r"[0-9]*", model.tokenizer) | # Restrict the logits to match the pattern
processors.temperature(0.5) | # Set temperature to 0.5
processors.logits_logging(model.tokenizer) # Log the restricted, temperature-augmentent, sampled logits
)
generator = outlines.generate.base(model, logits_processor)
generator("What is your favorite number? ")The error was
Traceback (most recent call last):
File "/home/cameron/dottxt/outlines/demo-logging.py", line 16, in <module>
generator("What is your favorite number? ")
File "/home/cameron/dottxt/outlines/outlines/generate/api.py", line 503, in __call__
completions = self.model.generate(
File "/home/cameron/dottxt/outlines/outlines/models/llamacpp.py", line 288, in generate
completion = self.model(prompts, **llama_cpp_params)
File "/home/cameron/dottxt/outlines/.venv/lib/python3.10/site-packages/llama_cpp/llama.py", line 1799, in __call__
return self.create_completion(
File "/home/cameron/dottxt/outlines/.venv/lib/python3.10/site-packages/llama_cpp/llama.py", line 1732, in create_completion
completion: Completion = next(completion_or_chunks) # type: ignore
File "/home/cameron/dottxt/outlines/.venv/lib/python3.10/site-packages/llama_cpp/llama.py", line 1216, in _create_completion
for token in self.generate(
File "/home/cameron/dottxt/outlines/.venv/lib/python3.10/site-packages/llama_cpp/llama.py", line 810, in generate
token = self.sample(
File "/home/cameron/dottxt/outlines/.venv/lib/python3.10/site-packages/llama_cpp/llama.py", line 704, in sample
else logits_processor(self._input_ids[: idx + 1], logits)
File "/home/cameron/dottxt/outlines/.venv/lib/python3.10/site-packages/llama_cpp/llama.py", line 2250, in __call__
scores = processor(input_ids, scores)
File "/home/cameron/dottxt/outlines/.venv/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
File "/home/cameron/dottxt/outlines/outlines/processors/base_logits_processor.py", line 82, in __call__
processed_logits = self.process_logits(
File "/home/cameron/dottxt/outlines/outlines/processors/base_logits_processor.py", line 168, in process_logits
result = processor.process_logits(input_ids, result)
File "/home/cameron/dottxt/outlines/outlines/processors/logging.py", line 63, in process_logits
self.logger.info(self.tokenizer.decode(input_ids))
File "/home/cameron/dottxt/outlines/outlines/models/llamacpp.py", line 56, in decode
decoded_bytes = self.tokenizer.detokenize(token_ids)
File "/home/cameron/dottxt/outlines/.venv/lib/python3.10/site-packages/llama_cpp/llama_tokenizer.py", line 52, in detokenize
return self._model.detokenize(tokens)
File "/home/cameron/dottxt/outlines/.venv/lib/python3.10/site-packages/llama_cpp/_internals.py", line 224, in detokenize
self.model, llama_cpp.llama_token(token), buffer, size, 0, special
TypeError: 'list' object cannot be interpreted as an integer| self.logger = logger | ||
| else: | ||
| self.logger = logging.getLogger("logits_logger") | ||
| self.logger.setLevel(logging.info) |
There was a problem hiding this comment.
I believe this should be
Suggested change
| self.logger.setLevel(logging.info) | |
| self.logger.setLevel(logging.INFO) |
| self.logger = logger | ||
| else: | ||
| self.logger = logging.getLogger("sequence_logger") | ||
| self.logger.setLevel(logging.info) |
There was a problem hiding this comment.
Suggested change
| self.logger.setLevel(logging.info) | |
| self.logger.setLevel(logging.INFO) |
|
Oh, also, the transformers output I think is the token indices, maybe |
|
Thanks for the review @cpfiffer ! It's a good refresher since I haven't looked at this in a while. I'll see if I have some free time this weekend and can get this ready for review in And indeed, it is token indices. Decoded tokens would be better. |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
No description provided.