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@dependabot dependabot bot commented on behalf of github Feb 28, 2022

Bumps numpy from 1.19.2 to 1.21.0.

Release notes

Sourced from numpy's releases.

v1.21.0

NumPy 1.21.0 Release Notes

The NumPy 1.21.0 release highlights are

  • continued SIMD work covering more functions and platforms,
  • initial work on the new dtype infrastructure and casting,
  • universal2 wheels for Python 3.8 and Python 3.9 on Mac,
  • improved documentation,
  • improved annotations,
  • new PCG64DXSM bitgenerator for random numbers.

In addition there are the usual large number of bug fixes and other improvements.

The Python versions supported for this release are 3.7-3.9. Official support for Python 3.10 will be added when it is released.

⚠️ Warning: there are unresolved problems compiling NumPy 1.21.0 with gcc-11.1 .

  • Optimization level -O3 results in many wrong warnings when running the tests.
  • On some hardware NumPy will hang in an infinite loop.

New functions

Add PCG64DXSM BitGenerator

Uses of the PCG64 BitGenerator in a massively-parallel context have been shown to have statistical weaknesses that were not apparent at the first release in numpy 1.17. Most users will never observe this weakness and are safe to continue to use PCG64. We have introduced a new PCG64DXSM BitGenerator that will eventually become the new default BitGenerator implementation used by default_rng in future releases. PCG64DXSM solves the statistical weakness while preserving the performance and the features of PCG64.

See upgrading-pcg64 for more details.

(gh-18906)

Expired deprecations

  • The shape argument numpy.unravel_index cannot be passed as dims keyword argument anymore. (Was deprecated in NumPy 1.16.)

... (truncated)

Commits
  • b235f9e Merge pull request #19283 from charris/prepare-1.21.0-release
  • 34aebc2 MAINT: Update 1.21.0-notes.rst
  • 493b64b MAINT: Update 1.21.0-changelog.rst
  • 07d7e72 MAINT: Remove accidentally created directory.
  • 032fca5 Merge pull request #19280 from charris/backport-19277
  • 7d25b81 BUG: Fix refcount leak in ResultType
  • fa5754e BUG: Add missing DECREF in new path
  • 61127bb Merge pull request #19268 from charris/backport-19264
  • 143d45f Merge pull request #19269 from charris/backport-19228
  • d80e473 BUG: Removed typing for == and != in dtypes
  • Additional commits viewable in compare view

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Bumps [numpy](https://github.com/numpy/numpy) from 1.19.2 to 1.21.0.
- [Release notes](https://github.com/numpy/numpy/releases)
- [Changelog](https://github.com/numpy/numpy/blob/main/doc/HOWTO_RELEASE.rst.txt)
- [Commits](numpy/numpy@v1.19.2...v1.21.0)

---
updated-dependencies:
- dependency-name: numpy
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot bot added dependencies Pull requests that update a dependency file python Pull requests that update Python code labels Feb 28, 2022
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Fixed by internal PR.

@chensuyue chensuyue closed this Mar 8, 2022
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dependabot bot commented on behalf of github Mar 8, 2022

OK, I won't notify you again about this release, but will get in touch when a new version is available. If you'd rather skip all updates until the next major or minor version, let me know by commenting @dependabot ignore this major version or @dependabot ignore this minor version.

If you change your mind, just re-open this PR and I'll resolve any conflicts on it.

@dependabot dependabot bot deleted the dependabot/pip/examples/pytorch/nlp/huggingface_models/common/examples/research_projects/lxmert/numpy-1.21.0 branch March 8, 2022 13:56
VincyZhang pushed a commit that referenced this pull request Feb 12, 2023
xin3he added a commit that referenced this pull request Feb 14, 2025
* [SW-20808] Make sure save&load format is an Enum object

Signed-off-by: Xin He <xinhe3@habana.ai>

* Update save_load_entry.py

---------

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>
Signed-off-by: Xin He <xinhe3@habana.ai>
yiliu30 pushed a commit that referenced this pull request Feb 14, 2025
* [SW-20808] Make sure save&load format is an Enum object

Signed-off-by: Xin He <xinhe3@habana.ai>

* Update save_load_entry.py

---------

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>
xin3he added a commit that referenced this pull request Feb 22, 2025
* [SW-20808] Make sure save&load format is an Enum object

Signed-off-by: Xin He <xinhe3@habana.ai>

* Update save_load_entry.py

---------

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>
Signed-off-by: Xin He <xinhe3@habana.ai>
XuehaoSun added a commit that referenced this pull request Feb 27, 2025
* [SW-210525] release HPU memory when loading neural_magic fp8 models (#48)

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>

* [SW-211178] save generation_config when saving model if exists (#57)

* [SW-211178] save generation_config when saving model if exists

---------

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>

* [SW-210543] update gitignore to simplify the git message (#50)

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>

* [SW-205334][SW-187731] llama70b vLLM fix graph breaks with  torch.compile (#67)

* fix graph breaks with torch.compile

* remove orig_mod from helper_modules

* fix typos

* fix test_register_apis

---------

Co-authored-by: Rafal Litka <rlitka@habana.ai>

* [SW-213890] Disable test_two_step_layer_wise temporarily (#84)

* [SW-205437] - Support LM-HEAD patching (#79)

* [SW-205437] - Support LM-HEAD patching

* fix CR comments

* Enhance and rename fix_measurements tool to postprocessing_vllm_measurements (#82)

* [SW-214088] Fix graph break caused by PatchedMixtralMoE (#74)

* [SW-208528] Support FP8 per channel Q/DQ (#13)

* add per channel qdq support

Signed-off-by: changwang <changwang@habana.ai>

* improve ut

Signed-off-by: changwang <changwang@habana.ai>

* improve get_scale_dtype func and qdq init

Signed-off-by: changwangss <changwang@habana.ai>

* improve DequantOutput QuantInput init

Signed-off-by: changwangss <changwang@habana.ai>

* add scale_method improve PCQ

Signed-off-by: changwangss <changwang@habana.ai>

* remove scale name

Signed-off-by: changwangss <changwang@habana.ai>

* fix PCQ scale_inv expanding

Signed-off-by: changwangss <changwang@habana.ai>

* merge the qdq_per_channel, qdq_per_tensor to qdq

Signed-off-by: changwangss <changwang@habana.ai>

* move scale_inv change to the QuantInput init

Signed-off-by: changwangss <changwang@habana.ai>

* remove  scale_dtype list judge

Signed-off-by: changwangss <changwang@habana.ai>

* fix missing axis parameter

Signed-off-by: changwangss <changwang@habana.ai>

---------

Signed-off-by: changwang <changwang@habana.ai>
Signed-off-by: changwangss <changwang@habana.ai>

* [SW-204341] explicit scale format for ops (#73)

* [SW-204341] explicit scale format for ops

Added wrapper around fp8 functions

Wrapper decides which flavor of the function to call,
according to scale format

Helper modules call the wrapper

Decide which cast flavor to call,
according to scale format

* [SW-204341] Adjust softmax API , remove commented-out code

* [SW-204341] Fixes from CR 1

* [SW-204341] Fixed CR 2

* [SW-204341] add missing arg is fsdpa

Signed-off-by: Uri Livne <ulivne@habana.ai>

* [SW-204341] Enhance SDPA for measure and quant

* [SW-204341] remove sdpa quantized ops

* reland per op class with more enchancments

* [SW-204341] reland specfic arguments , rename class to wrapper

* added call with self in patched lm head

rebased on top of master next
force push

* fix mistake in conflict resolution

resotore MethodType fix

* antoher fix

* modified fp8 mtamul test to test quantized matmul func

* another fix of rebase mistake

* hopefully last rebase mistake fix

* restore backward compatibly import protection

---------

Signed-off-by: Uri Livne <ulivne@habana.ai>

* [SW-213890] Revert "[SW-213890] Disable test_two_step_layer_wise temporarily (#84)" (#86)

This reverts commit 27162ae.

* Revert "[SW-205334][SW-187731] llama70b vLLM fix graph breaks with  torch.com…" (#87)

This reverts commit 01a5734.

Co-authored-by: Danny Semiat <dsemiat@habana.ai>

* [ALGO-809] PatchedLmHeadLinearAllreduce: replacing the sharding code with the one from deepspeed-fork (#85)

Change-Id: Icb9670cfefdd1880c1ebb9a804a97c9ba79ecdc3

Co-authored-by: smarkovichgolan <smarkovich@habana.ai>

* fix bug of FusedMoE object has no attribute w13_weight (#94)

Signed-off-by: yuwenzho <yuwen.zhou@intel.com>

* [SW-208588] Add HPU fp8 Dynamic MOE (#88)

* [SW-208588] Add HPU fp8 Dynamic MOE

* fix review comments

* fix more review comments

* fix comments

* fix tests

* minor config fixes (#96)

* [SW-0] minor cosmetic fixes in quant_config

* remove hooks

* [SW-196641] - Fix type mismatch in linear quantization unit tests (#99)

* [SW-196641] - Fix type mismatch in linear quantization unit tests

* fix atol value

* add hp_dtype to fp8 config dict before parsing

* [SW-214785] Apply PatchedModuleBase for all existing PatchedModules (#92)

* [SW-214785] Apply PatchedModuleBase for all existing PatchedModules

Signed-off-by: Xin He <xinhe3@habana.ai>

---------

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>

* [SW-215319] threshold of memory usage in test_block_wise.py is too tight (#100)

* [SW-215543] Revert "minor config fixes (#96)" (#104)

This reverts commit fa40142.

* fix RowParalleLinear func names from string to tuple (#106)

* [SW-215615] memory is unreleased during loading neural_magic models on multi-cards (#105)

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>

* [SW-212423] RuntimeError when load the gptq model from HF (#70)

* [SW-212423] RuntimeError when load the gptq model from HF
* skip tie_word_embeddings=False

Signed-off-by: Xin He <xinhe3@habana.ai>

---------

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>

* [SW-214785] fix issue when self._mod_extra_config is None (#108)

* [SW-211826] [example] demonstrate layer-wise, block-wise and lm_eval usage (#66)

* [SW-211826] [example] demonstrate layer-wise&block-wise usage to quantize LLM with limited host&device memory

Signed-off-by: Xin He <xinhe3@habana.ai>

---------

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>

* [SW-215295] Force single object from quantized func wrapper classes (#103)

* [SW-215295] Force single object from quantized func wrapper classes

* Modify the factory object to be cleared after module patching

* Move cleanup to Quantizer object

* [SW-216292]Minor update for lm-eval (#113)

* Enable lm-eval 0.4.2 and expose `add_bos_token`

---------

Signed-off-by: Yi Liu <yiliu4@habana.ai>
Co-authored-by: Yi Liu <yiliu4@habana.ai>

* [SW-209207] add vllm fp8 dynamic MoE (#116)

* [SW-216239] Align Softmax fp8 scale calc with configuration (#112)

* [SW-217321] Skip auto round tests (#119) (#125)

* Test Commit

* [SW-217321] Skip auto round tests do to CI breakage

* remove uneeded print

* [SW-207451] Implement block-wise calibration for LLM (#24)

For LLMs, measurement on bf16 requires high hpu memory usage.
This change can help measure bf16 llama-405b on 8 Gaudi2 card, or measure llama-70b on 1 Gaudi card.
Shortage: cannot measure lm_head layer, maybe we can enhance it later.

---------

Signed-off-by: Xin <xin3.he@intel.com>
Co-authored-by: Xin He <xinhe3@habana.ai>
Signed-off-by: Xin He <xinhe3@habana.ai>

* [SW-197077] fix bug in output arbitrary scales (#45)

* [SW-197077] fix bug

* [SW-197077] fix bug in outputs arbitrary scales

Signed-off-by: Xin He <xinhe3@habana.ai>

* [SW-197077] fix bug in output arbitrary scales (#45)

* [SW-197077] fix bug

* [SW-197077] fix bug in outputs arbitrary scales

* [SW-210500] [Optimum-Habana] [Regression] [fp8] [INC] No generated text for llava models [llava-1.5-7b-hf] [llava-1.5-13b-hf ] (#54) (#77)

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>

* [SW-213236] resolve CPU mem issue in CI (#76) (#83)

Cherry-pick from 1.19
Co-authored-by: Xin He <xin3.he@intel.com>

* [SW-213368] requirements_pt.txt: allow newer pydantic versions to >= 1.10.13 (#80)

* requirements_pt.txt: upgrade pydantic version to >= 2.0.0

* allow newer version of pydantic

newer deepspeed uses pydantic v2, which have slight different APIs.

* Update requirements_pt.txt

* [SW-212057] Enable scalar scale to support QDQ (#98)

* [SW-212057] Enable scalar scale to support QDQ

Change-Id: Ib5f5accd7a770675609e91c18bd04497b15937c5

* PR comment fixes

Change-Id: I01be41c29721b8d59c887f3d2b4e3cef8433331c
Signed-off-by: Xin He <xinhe3@habana.ai>

* [SW-215845] Run some unit tests from top level API (#109)

Signed-off-by: Xin He <xinhe3@habana.ai>

* [SW-212629] Support saving weight-only quantization INT4 model in Hugging Face format (#101)

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>
Signed-off-by: Xin He <xinhe3@habana.ai>

* [SW-205970] update state_dict to save scalar scales (#6)

* update state_dict method in save/load function

---------

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>
Signed-off-by: Xin He <xinhe3@habana.ai>

* Revert "[SW-205970] update state_dict to save scalar scales (#6)" (#114)

This reverts commit ffcb97e.

* [SW-212092] Save vllm compatible format (#102)

* save vllm compatible format

Signed-off-by: changwangss <changwang@habana.ai>

* add assertion and improve max_file_size to human reading

Signed-off-by: changwangss <changwang@habana.ai>

* support default the same with huggingface when saving

Signed-off-by: changwangss <changwang@habana.ai>

* separate save funtion for single device and multi devices.

Signed-off-by: changwangss <changwang@habana.ai>

* rebase

Signed-off-by: changwangss <changwang@habana.ai>

* rebase save

Signed-off-by: changwangss <changwang@habana.ai>

* remove weight and scale convert on G2

Signed-off-by: changwangss <changwang@habana.ai>

* rebase master_next due to revert #6

Signed-off-by: changwangss <changwang@habana.ai>

* improve convert weight to vllm compatable function

Signed-off-by: changwangss <changwang@habana.ai>

* replace print to logger

Signed-off-by: changwangss <changwang@habana.ai>

* move unit_mapping to common utils

Signed-off-by: changwangss <changwang@habana.ai>

---------

Signed-off-by: changwangss <changwang@habana.ai>
Signed-off-by: Xin He <xinhe3@habana.ai>

* [SW-205970] update state_dict to save scalar scales (#115)

* [SW-205970] update state_dict to save scalar scales (#6)

* update state_dict method in save/load function

* support mixtral
---------

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>

* [SW-215009] support loading per-channel scales (#95)

* [SW-215009] support loading per-channel scales

Signed-off-by: Xin He <xinhe3@habana.ai>

* fix UT

Signed-off-by: Xin He <xinhe3@habana.ai>

---------

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>

* Refactoring scales (#22) (#122)

* Refactoring scales (#22)

* [SW-197077] refactoring maxabs scales and adding arbitrary scales.

* [SW-199696] Supporting Dynamic Quantization (#128)

* Calculating dynamic scales using nn.Modules

Change-Id: I8c344ae737803b39117037edaaa3d3b9cbd09f30

* [SW-199696] Supporting Dynamic Quantization

Change-Id: Ic5d6f04ec0b5032ac305e1b3097747c47250385b

* Code cleanup

Change-Id: I213bc7438e06bd1002775066bfb0dc6f10e8a84a

* Review changes and model print issue (circular dependency fix)

Change-Id: I5c41d2f9a937416ce260f55cb045c86858dd201a

* removed debug code from patching_common.py

* Round 2 + CI import issue

Change-Id: I27dbb33de8e027fb0b726336b38156b5d23a6896
Signed-off-by: Xin He <xinhe3@habana.ai>

* [SW-217334] enable fp8 qdq mode using PatchedModuleBase (#129)

* [SW-217334] enable fp8 qdq mode using PatchedModuleBase

* fix review commnets

* [SW-218871] fp8 multi-cards is not loaded correctly (#138)

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>

* Fix bug in mixtral unitscale (#141)

* [SW-218197] fix bug in Mixtral unitscale

* [SW-218197] fix bug in Mixtral unitscale

* update version to 3.3 for release

Signed-off-by: Xin He <xinhe3@habana.ai>

* [SW-20808] Make sure save&load format is an Enum object (#58)

* [SW-20808] Make sure save&load format is an Enum object

Signed-off-by: Xin He <xinhe3@habana.ai>

* Update save_load_entry.py

---------

Signed-off-by: Xin He <xinhe3@habana.ai>
Co-authored-by: Xin He <xinhe3@habana.ai>
Signed-off-by: Xin He <xinhe3@habana.ai>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* add xfail for torchvision

Signed-off-by: Xin He <xinhe3@habana.ai>

* fix ILITV-3859

Signed-off-by: xin3he <xin3.he@intel.com>

* workaround for ILITV-3858

Signed-off-by: xin3he <xin3.he@intel.com>

* fix sdxl_smooth_quant

Signed-off-by: xin3he <xin3.he@intel.com>

* fix ILITV-3854

Signed-off-by: xin3he <xin3.he@intel.com>

---------

Signed-off-by: Xin He <xinhe3@habana.ai>
Signed-off-by: changwang <changwang@habana.ai>
Signed-off-by: changwangss <changwang@habana.ai>
Signed-off-by: Uri Livne <ulivne@habana.ai>
Signed-off-by: yuwenzho <yuwen.zhou@intel.com>
Signed-off-by: Yi Liu <yiliu4@habana.ai>
Signed-off-by: Xin <xin3.he@intel.com>
Signed-off-by: xin3he <xin3.he@intel.com>
Co-authored-by: Xin He <xinhe3@habana.ai>
Co-authored-by: RafLit <rafal.litka@intel.com>
Co-authored-by: Rafal Litka <rlitka@habana.ai>
Co-authored-by: Dany Kiazada <141814181+kiazada@users.noreply.github.com>
Co-authored-by: Nir David <124874956+nirda7@users.noreply.github.com>
Co-authored-by: Yuwen Zhou <yuwen.zhou@intel.com>
Co-authored-by: Wang, Chang <changwang@habana.ai>
Co-authored-by: Uri Livne <ulivne@habana.ai>
Co-authored-by: Oz Abramovich <oabramovich@habana.ai>
Co-authored-by: Dudi Lester <160421192+dudilester@users.noreply.github.com>
Co-authored-by: Danny Semiat <dsemiat@habana.ai>
Co-authored-by: smarkovichgolan <smarkovich@habana.ai>
Co-authored-by: Yi Liu <yi4.liu@intel.com>
Co-authored-by: Yi Liu <yiliu4@habana.ai>
Co-authored-by: Linoy Buchnik <linoybu@gmail.com>
Co-authored-by: Nadav Elyahu <88962733+nelyahu@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: chen, suyue <suyue.chen@intel.com>
Co-authored-by: Sun, Xuehao <xuehao.sun@intel.com>
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