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2lambda123 / pytorch-serve

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Bump the pip group across 3 directories with 3 updates #31

Closed dependabot[bot] closed 6 months ago

dependabot[bot] commented 7 months ago

Bumps the pip group with 1 update in the /examples/large_models/Huggingface_accelerate/llama2 directory: transformers. Bumps the pip group with 1 update in the /examples/large_models/inferentia2/llama2/continuous_batching directory: transformers. Bumps the pip group with 2 updates in the /requirements directory: pillow and onnx.

Updates transformers from 4.36.0 to 4.38.0

Release notes

Sourced from transformers's releases.

v4.38: Gemma, Depth Anything, Stable LM; Static Cache, HF Quantizer, AQLM

New model additions

💎 Gemma 💎

Gemma is a new opensource Language Model series from Google AI that comes with a 2B and 7B variant. The release comes with the pre-trained and instruction fine-tuned versions and you can use them via AutoModelForCausalLM, GemmaForCausalLM or pipeline interface!

Read more about it in the Gemma release blogpost: https://hf.co/blog/gemma

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b")
model = AutoModelForCausalLM.from_pretrained("google/gemma-2b", device_map="auto", torch_dtype=torch.float16)


input_text = "Write me a poem about Machine Learning."
input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")


outputs = model.generate(**input_ids)

You can use the model with Flash Attention, SDPA, Static cache and quantization API for further optimizations !

  • Flash Attention 2
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b")


model = AutoModelForCausalLM.from_pretrained(
"google/gemma-2b", device_map="auto", torch_dtype=torch.float16, attn_implementation="flash_attention_2"
)


input_text = "Write me a poem about Machine Learning."
input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")


outputs = model.generate(**input_ids)

  • bitsandbytes-4bit
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b")


model = AutoModelForCausalLM.from_pretrained(
"google/gemma-2b", device_map="auto", load_in_4bit=True
)
</tr></table>

... (truncated)

Commits
  • 08ab54a [ gemma] Adds support for Gemma 💎 (#29167)
  • 2de9314 [Maskformer] safely get backbone config (#29166)
  • 476957b 🚨 Llama: update rope scaling to match static cache changes (#29143)
  • 7a4bec6 Release: 4.38.0
  • ee3af60 Add support for fine-tuning CLIP-like models using contrastive-image-text exa...
  • 0996a10 Revert low cpu mem tie weights (#29135)
  • 15cfe38 [Core tokenization] add_dummy_prefix_space option to help with latest is...
  • efdd436 FIX [PEFT / Trainer ] Handle better peft + quantized compiled models (#29...
  • 5e95dca [cuda kernels] only compile them when initializing (#29133)
  • a7755d2 Generate: unset GenerationConfig parameters do not raise warning (#29119)
  • Additional commits viewable in compare view


Updates transformers from 4.36.2 to 4.38.0

Release notes

Sourced from transformers's releases.

v4.38: Gemma, Depth Anything, Stable LM; Static Cache, HF Quantizer, AQLM

New model additions

💎 Gemma 💎

Gemma is a new opensource Language Model series from Google AI that comes with a 2B and 7B variant. The release comes with the pre-trained and instruction fine-tuned versions and you can use them via AutoModelForCausalLM, GemmaForCausalLM or pipeline interface!

Read more about it in the Gemma release blogpost: https://hf.co/blog/gemma

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b")
model = AutoModelForCausalLM.from_pretrained("google/gemma-2b", device_map="auto", torch_dtype=torch.float16)


input_text = "Write me a poem about Machine Learning."
input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")


outputs = model.generate(**input_ids)

You can use the model with Flash Attention, SDPA, Static cache and quantization API for further optimizations !

  • Flash Attention 2
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b")


model = AutoModelForCausalLM.from_pretrained(
"google/gemma-2b", device_map="auto", torch_dtype=torch.float16, attn_implementation="flash_attention_2"
)


input_text = "Write me a poem about Machine Learning."
input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")


outputs = model.generate(**input_ids)

  • bitsandbytes-4bit
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b")


model = AutoModelForCausalLM.from_pretrained(
"google/gemma-2b", device_map="auto", load_in_4bit=True
)
</tr></table>

... (truncated)

Commits
  • 08ab54a [ gemma] Adds support for Gemma 💎 (#29167)
  • 2de9314 [Maskformer] safely get backbone config (#29166)
  • 476957b 🚨 Llama: update rope scaling to match static cache changes (#29143)
  • 7a4bec6 Release: 4.38.0
  • ee3af60 Add support for fine-tuning CLIP-like models using contrastive-image-text exa...
  • 0996a10 Revert low cpu mem tie weights (#29135)
  • 15cfe38 [Core tokenization] add_dummy_prefix_space option to help with latest is...
  • efdd436 FIX [PEFT / Trainer ] Handle better peft + quantized compiled models (#29...
  • 5e95dca [cuda kernels] only compile them when initializing (#29133)
  • a7755d2 Generate: unset GenerationConfig parameters do not raise warning (#29119)
  • Additional commits viewable in compare view


Updates pillow from 10.2.0 to 10.3.0

Release notes

Sourced from pillow's releases.

10.3.0

https://pillow.readthedocs.io/en/stable/releasenotes/10.3.0.html

Changes

... (truncated)

Changelog

Sourced from pillow's changelog.

10.3.0 (2024-04-01)

  • CVE-2024-28219: Use strncpy to avoid buffer overflow #7928 [radarhere, hugovk]

  • Deprecate eval(), replacing it with lambda_eval() and unsafe_eval() #7927 [radarhere, hugovk]

  • Raise ValueError if seeking to greater than offset-sized integer in TIFF #7883 [radarhere]

  • Add --report argument to __main__.py to omit supported formats #7818 [nulano, radarhere, hugovk]

  • Added RGB to I;16, I;16L, I;16B and I;16N conversion #7918, #7920 [radarhere]

  • Fix editable installation with custom build backend and configuration options #7658 [nulano, radarhere]

  • Fix putdata() for I;16N on big-endian #7209 [Yay295, hugovk, radarhere]

  • Determine MPO size from markers, not EXIF data #7884 [radarhere]

  • Improved conversion from RGB to RGBa, LA and La #7888 [radarhere]

  • Support FITS images with GZIP_1 compression #7894 [radarhere]

  • Use I;16 mode for 9-bit JPEG 2000 images #7900 [scaramallion, radarhere]

  • Raise ValueError if kmeans is negative #7891 [radarhere]

  • Remove TIFF tag OSUBFILETYPE when saving using libtiff #7893 [radarhere]

  • Raise ValueError for negative values when loading P1-P3 PPM images #7882 [radarhere]

  • Added reading of JPEG2000 palettes #7870 [radarhere]

  • Added alpha_quality argument when saving WebP images #7872 [radarhere]

... (truncated)

Commits
  • 5c89d88 10.3.0 version bump
  • 63cbfcf Update CHANGES.rst [ci skip]
  • 2776126 Merge pull request #7928 from python-pillow/lcms
  • aeb51cb Merge branch 'main' into lcms
  • 5beb0b6 Update CHANGES.rst [ci skip]
  • cac6ffa Merge pull request #7927 from python-pillow/imagemath
  • f5eeeac Name as 'options' in lambda_eval and unsafe_eval, but '_dict' in deprecated eval
  • facf3af Added release notes
  • 2a93aba Use strncpy to avoid buffer overflow
  • a670597 Update CHANGES.rst [ci skip]
  • Additional commits viewable in compare view


Updates onnx from 1.14.1 to 1.16.0

Release notes

Sourced from onnx's releases.

v1.16.0

ONNX v1.16.0 is now available with exciting new features! We would like to thank everyone who contributed to this release! Please visit onnx.ai to learn more about ONNX and associated projects.

Key Updates

ai.onnx Opset 21

ai.onnx.ml Opset 4

IR Version 10

  • Added support for UINT4, INT4 types
  • GraphProto, FunctionProto, NodeProto, TensorProto added metadata_props field
  • FunctionProto added value_info field
  • FunctionProto and NodeProto added overload field to support overloaded functions.

Python Changes

  • Support registering custom OpSchemas via Python interface
  • Support Python3.12

Security Updates

  • Fix path sanitization bypass leading to arbitrary read (CVE-2024-27318)
  • Fix Out of bounds read due to lack of string termination in assert (CVE-2024-27319)

Deprecation notice

Bug fixes and infrastructure improvements

  • Enable empty list of values as attribute (#5559)
  • Add backward conversions from 18->17 for reduce ops (#5606)
  • DFT-20 version converter (#5613)
  • Fix version-converter to generate valid identifiers (#5628)
  • Reserve removed proto fields (#5643)
  • Cleanup shape inference implementation (#5596)
  • Do not use LFS64 on non-glibc linux (#5669)
  • Drop "one of" default attribute check in LabelEncoder (#5673)
  • TreeEnsemble base values for the reference implementation (#5665)
  • Parser/printer support external data format (#5688)
  • [cmake] Place export target file in the correct directory (#5677)

... (truncated)

Commits


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performance-testing-bot[bot] commented 7 months ago

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git-greetings[bot] commented 7 months ago

Thanks @dependabot[bot] for opening this PR!

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code-companion-ai[bot] commented 7 months ago

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Micro-Learning Topic: Buffer overflow (Detected by phrase)

Matched on "buffer overflow"

What is this? (2min video)

A buffer overflow condition exists when a program attempts to put more data in a buffer than it can hold or when a program attempts to put data in a memory area past a buffer.

Try a challenge in Secure Code Warrior

codesyncapp[bot] commented 7 months ago

Check out the playback for this Pull Request here.

git-greetings[bot] commented 7 months ago
PR Details of @dependabot[bot] in pytorch-serve : OPEN CLOSED TOTAL
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socket-security[bot] commented 7 months ago

New and removed dependencies detected. Learn more about Socket for GitHub ↗︎

Package New capabilities Transitives Size Publisher
pypi/grpcio-tools@1.62.1 environment, eval 0 22.1 MB google_opensource, grpc-packages
pypi/transformers@4.38.0 environment, eval, filesystem, network, shell, unsafe 0 39.5 MB ArthurZucker, Thomwolf, amysartran, ...2 more

🚮 Removed packages: pypi/transformers@4.36.0, pypi/transformers@4.36.0, pypi/transformers@4.36.2, pypi/transformers@4.36.2

View full report↗︎

dependabot[bot] commented 6 months ago

Superseded by #39.