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pyproject.toml
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pyproject.toml
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[build-system]
requires = ["flit_core >=3.2,<4"]
build-backend = "flit_core.buildapi"
[project]
name = "axlearn"
version = "0.1.1"
description = "AXLearn"
readme = "README.md"
requires-python = ">=3.9"
# Production dependencies.
# Minimal requirments for axlearn/common/config.py.
dependencies = [
"attrs>=23.1.0", # We use `type` in `attrs.field`
"numpy==1.26.4", # verified with tensorflow 2.14 RaggedTensor
]
[project.optional-dependencies]
# Core dependencies needed for jax based training and evaluation.
# Every time we upgrade JAX, we should try to bring the rest to the newest versions.
core = [
"absl-py==2.1.0",
"chex==0.1.86", # chex 0.1.86 is required for jax 0.4.25.
"importlab==0.7", # breaks pytype on 0.8
"jax==0.4.30",
"jaxlib==0.4.30",
"nltk==3.7", # for text preprocessing
"optax==0.1.7", # optimizers (0.1.0 has known bugs).
"portpicker",
"protobuf>=3.20.3",
"tensorboard-plugin-profile==2.15.1",
# This has both x86 and arm64 wheels. Underneath the hood it uses tensorflow-macos since 2.13.
"tensorflow==2.16.1",
"tensorflow-datasets>=4.9.2",
"tensorflow-io>=0.37.1", # for tensorflow-2.16. Note that 0.37.0 results in "pure virtual method called".
"tensorflow_text==2.16.1; platform_machine == 'x86_64'", # implied by seqio, but also used directly for text processing
"tensorstore>=0.1.63", # used for supporting GDA checkpoints
"toml", # for config management
"typing-extensions==4.11.0",
"scipy==1.12.0", # to avoid "module 'scipy.linalg' has no attribute 'tril'"
"seqio==0.0.18", # used for inputs
"aqtp==0.4.0", # aqtp>=0.5.0 requires python>=3.10 due to the use of Union shorthand "|" in type hints.
"flax==0.8.5", # for AQT, param converter and adapter.
"prefixed==0.7.1", # For formatting file sizes, param counts, etc.
]
# Apple Silicon dependencies.
# Need to run `conda install -c apple tensorflow-deps` separately.
apple-silicon = [
"tensorflow-metal==1.1.0; platform_machine == 'arm64'",
# As of Nov 15, 2023, tensorflow_text has no arm64 build.
# We need to manually build the wheel and install it, following instructions at https://github.com/tensorflow/text/tree/2.14#build-from-source-steps.
]
# Requirements for testing and development.
dev = [
"axlearn[orbax]", # checkpointer tests
"black==23.1a1", # formatting
"einops",
"evaluate",
"isort", # formatting
"pre-commit", # local pre commit hooks
"pycocotools", # COCO evaluation tools
"pylint==2.17.7",
"pytest", # test runner
"pytest-xdist", # pytest plugin for test parallelism
"pytype==2022.4.22", # type checking
"scikit-learn>=1.1.1", # test-only
# Fix AttributeError: module 'scipy.linalg' has no attribute 'tril' and related scipy import errors.
"scipy==1.12.0",
"sentencepiece != 0.1.92",
"tqdm", # test-only
"timm==0.6.12", # DiT Dependency test-only
"torch>=1.12.1", # test-only
"torchvision==0.16.1", # test-only
"transformers==4.44.1", # test-only
"wandb", # test-only
"wrapt", # implied by tensorflow-datasets, but also used in config tests.
]
# Requirements for GCP job management.
gcp = [
"cloud-tpu-client", # for creating and managing TPUs.
"crcmod", # for file uploads.
"kubernetes",
"google-api-core==2.17.1",
"google-api-python-client==2.109.0",
"google-auth==2.29.0",
"google-auth[pyopenssl]", # Ensures that we have compatible pyopenssl/cryptography pins.
"google-cloud-storage==2.16.0",
"google-cloud-core==2.3.3",
"google-cloud-build==3.24.1",
"ml_goodput_measurement==0.0.2",
"pyOpenSSL>=22.1.0", # compat with cryptography version.
]
# For TPU training.
# Note: Specify -f https://storage.googleapis.com/jax-releases/libtpu_releases.html during install.
tpu = [
"axlearn[gcp]",
"jax[tpu]==0.4.30", # must be >=0.4.19 for compat with v5p.
]
# Vertex AI tensorboard.
vertexai_tensorboard = [
# Required to fix a `distro-info` bug we run into when using `tb_gcp_tensorboard` from
# `google_cloud_aiplatform[tensorboard]`. See:
# [1] https://bugs.launchpad.net/ubuntu/+source/distro-info/+bug/1991606
# [2] https://github.com/pypa/setuptools/issues/3772
"setuptools==65.7.0",
# Pin version to fix Tensorboard uploader TypeError: can only concatenate str (not "NoneType") to str
# https://github.com/googleapis/python-aiplatform/commit/4f982ab254b05fe44a9d2ed959fca2793961b56c
"google-cloud-aiplatform[tensorboard]==1.61.0",
"tensorboard",
]
# Dataflow dependencies.
dataflow = [
"apache-beam==2.55.1",
"apache-beam[gcp]",
"google-apitools", # for beam pipeline
"orjson==3.9.10",
]
# GPU custom kernel dependency.
gpu = [
"triton==2.1.0",
"jax[cuda12_pip]==0.4.30",
]
# Open API inference.
open_api = [
"openai==1.35.1",
]
# MMAU benchmark.
mmau = [
"openai==1.35.14",
"anthropic==0.31.2",
"nbformat==5.10.4",
"plotly==5.22.0",
"nbconvert==7.16.4",
"google-cloud-aiplatform==1.50.0",
"transformers==4.44.1",
]
# Orbax checkpointing.
orbax = [
"humanize==4.10.0",
"orbax-checkpoint==0.5.23",
]
[tool.flit.module]
# This defines the import name. https://flit.pypa.io/en/stable/pyproject_toml.html#module-section
name = "axlearn"
[project.scripts]
# Entrypoint for CLI.
axlearn = "axlearn.cli:main"
[tool.black]
line-length = 100
target-version = ['py38', 'py39']
[tool.ruff]
line-length = 100
target-version = 'py39'
[tool.pytest.ini_options]
addopts = "-rs -s -p no:warnings --junitxml=test-results/testing.xml"
markers = [
"gs_login: tests needing GS login.",
"tpu: tests needing access to a TPU device.",
"high_cpu: tests that require a lot of CPU.",
"fp64: tests that require 64-bit floating point precision.",
"golden_config: golden config tests.",
"golden_init: golden init tests.",
"golden_regularizer: golden regularizer scale tests.",
"golden_param_update: golden param update scale tests.",
]
testpaths = "."
junit_family="xunit2"
[tool.isort]
line_length = 100
profile = "black"