requirements-ci.txt

# Python dependencies required for unit tests

#awscli==1.6 #this breaks some platforms
#Description: AWS command line interface
#Pinned versions: 1.6
#test that import:

boto3==1.35.42
#Description: AWS SDK for python
#Pinned versions: 1.19.12, 1.16.34
#test that import:

click
#Description: Command Line Interface Creation Kit
#Pinned versions:
#test that import:

coremltools==5.0b5 ; python_version < "3.12"
coremltools==8.3 ; python_version == "3.12"
#Description: Apple framework for ML integration
#Pinned versions: 5.0b5
#test that import:

#dataclasses #this breaks some platforms
#Description: Provides decorators for auto adding special methods to user classes
#Pinned versions:
#test that import:

dill==0.3.7
#Description: dill extends pickle with serializing and de-serializing for most built-ins
#Pinned versions: 0.3.7
#test that import: dynamo/test_replay_record.py test_dataloader.py test_datapipe.py test_serialization.py

expecttest==0.3.0
#Description: method for writing tests where test framework auto populates
# the expected output based on previous runs
#Pinned versions: 0.3.0
#test that import:

fbscribelogger==0.1.7
#Description: write to scribe from authenticated jobs on CI
#Pinned versions: 0.1.6
#test that import:

flatbuffers==24.12.23
#Description: cross platform serialization library
#Pinned versions: 24.12.23
#test that import:

hypothesis==5.35.1
# Pin hypothesis to avoid flakiness: https://github.com/pytorch/pytorch/issues/31136
#Description: advanced library for generating parametrized tests
#Pinned versions: 5.35.1
#test that import: test_xnnpack_integration.py, test_pruning_op.py, test_nn.py

junitparser==2.1.1
#Description: unitparser handles JUnit/xUnit Result XML files
#Pinned versions: 2.1.1
#test that import:

lark==0.12.0
#Description: parser
#Pinned versions: 0.12.0
#test that import:

librosa>=0.6.2 ; python_version < "3.11" and platform_machine != "s390x"
librosa==0.10.2 ; python_version == "3.12" and platform_machine != "s390x"
#Description: A python package for music and audio analysis
#Pinned versions: >=0.6.2
#test that import: test_spectral_ops.py
#librosa depends on numba; disable it for s390x while numba is disabled too

#mkl #this breaks linux-bionic-rocm4.5-py3.7
#Description: Intel oneAPI Math Kernel Library
#Pinned versions:
#test that import: test_profiler.py, test_public_bindings.py, test_testing.py,
#test_nn.py, test_mkldnn.py, test_jit.py, test_fx_experimental.py,
#test_autograd.py

#mkl-devel
# see mkl

#mock
#Description: A testing library that allows you to replace parts of your
#system under test with mock objects
#Pinned versions:
#test that import: test_modules.py, test_nn.py,
#test_testing.py

#MonkeyType # breaks pytorch-xla-linux-bionic-py3.7-clang8
#Description: collects runtime types of function arguments and return
#values, and can automatically generate stub files
#Pinned versions:
#test that import:

mypy==1.16.0 ; platform_system != "Windows"
# Pin MyPy version because new errors are likely to appear with each release
# Skip on Windows as lots of type annotations are POSIX specific
#Description: linter
#Pinned versions: 1.16.0
#test that import: test_typing.py, test_type_hints.py

networkx==2.8.8
#Description: creation, manipulation, and study of
#the structure, dynamics, and functions of complex networks
#Pinned versions: 2.8.8
#test that import: functorch

ninja==1.11.1.3
#Description: build system. Used in some tests. Used in build to generate build
#time tracing information
#Pinned versions: 1.11.1.3
#test that import: run_test.py, test_cpp_extensions_aot.py,test_determination.py

numba==0.60.0 ; python_version == "3.9"
numba==0.61.2 ; python_version > "3.9"
#Description: Just-In-Time Compiler for Numerical Functions
#Pinned versions: 0.54.1, 0.49.0, <=0.49.1
#test that import: test_numba_integration.py
#For numba issue see https://github.com/pytorch/pytorch/issues/51511
#Need release > 0.61.2 for s390x due to https://github.com/numba/numba/pull/10073

#numpy
#Description: Provides N-dimensional arrays and linear algebra
#Pinned versions: 1.26.2
#test that import: test_view_ops.py, test_unary_ufuncs.py, test_type_promotion.py,
#test_type_info.py, test_torch.py, test_tensorexpr_pybind.py, test_tensorexpr.py,
#test_tensorboard.py, test_tensor_creation_ops.py, test_static_runtime.py,
#test_spectral_ops.py, test_sort_and_select.py, test_shape_ops.py,
#test_segment_reductions.py, test_reductions.py, test_pruning_op.py,
#test_overrides.py, test_numpy_interop.py, test_numba_integration.py
#test_nn.py, test_namedtensor.py, test_linalg.py, test_jit_cuda_fuser.py,
#test_jit.py, test_indexing.py, test_datapipe.py, test_dataloader.py,
#test_binary_ufuncs.py
numpy==2.0.2 ; python_version == "3.9"
numpy==2.1.2 ; python_version > "3.9"

pandas==2.2.3

#onnxruntime
#Description: scoring engine for Open Neural Network Exchange (ONNX) models
#Pinned versions: 1.9.0
#test that import:

opt-einsum==3.3
#Description: Python library to optimize tensor contraction order, used in einsum
#Pinned versions: 3.3
#test that import: test_linalg.py

optree==0.13.0
#Description: A library for tree manipulation
#Pinned versions: 0.13.0
#test that import: test_vmap.py, test_aotdispatch.py, test_dynamic_shapes.py,
#test_pytree.py, test_ops.py, test_control_flow.py, test_modules.py,
#common_utils.py, test_eager_transforms.py, test_python_dispatch.py,
#test_expanded_weights.py, test_decomp.py, test_overrides.py, test_masked.py,
#test_ops.py, test_prims.py, test_subclass.py, test_functionalization.py,
#test_schema_check.py, test_profiler_tree.py, test_meta.py, test_torchxla_num_output.py,
#test_utils.py, test_proxy_tensor.py, test_memory_profiler.py, test_view_ops.py,
#test_pointwise_ops.py, test_dtensor_ops.py, test_torchinductor.py, test_fx.py,
#test_fake_tensor.py, test_mps.py

pillow==11.0.0
#Description:  Python Imaging Library fork
#Pinned versions: 10.3.0
#test that import:

protobuf==5.29.4
#Description:  Google's data interchange format
#Pinned versions: 5.29.4
#test that import: test_tensorboard.py, test/onnx/*


psutil
#Description: information on running processes and system utilization
#Pinned versions:
#test that import: test_profiler.py, test_openmp.py, test_dataloader.py

pytest==7.3.2
#Description: testing framework
#Pinned versions:
#test that import: test_typing.py, test_cpp_extensions_aot.py, run_test.py

pytest-xdist==3.3.1
#Description: plugin for running pytest in parallel
#Pinned versions:
#test that import:

pytest-flakefinder==1.1.0
#Description: plugin for rerunning tests a fixed number of times in pytest
#Pinned versions: 1.1.0
#test that import:

pytest-rerunfailures>=10.3
#Description: plugin for rerunning failure tests in pytest
#Pinned versions:
#test that import:

pytest-subtests==0.13.1
#Description: plugin for subtest support
#Pinned versions:
#test that import:

#pytest-benchmark
#Description: fixture for benchmarking code
#Pinned versions: 3.2.3
#test that import:

#pytest-sugar
#Description: shows failures and errors instantly
#Pinned versions:
#test that import:

xdoctest==1.1.0
#Description: runs doctests in pytest
#Pinned versions: 1.1.0
#test that import:

pygments==2.15.0
#Description: support doctest highlighting
#Pinned versions: 2.12.0
#test that import: the doctests

#pyyaml
#Description: data serialization format
#Pinned versions: 6.0.2
#test that import:

#requests
#Description: HTTP library
#Pinned versions:
#test that import: test_type_promotion.py

#rich
#Description: rich text and beautiful formatting in the terminal
#Pinned versions: 14.1.0
#test that import:

scikit-image==0.19.3 ; python_version < "3.10"
scikit-image==0.22.0 ; python_version >= "3.10"
#Description: image processing routines
#Pinned versions:
#test that import: test_nn.py

#scikit-learn
#Description: machine learning package
#Pinned versions: 0.20.3
#test that import:

scipy==1.13.1 ; python_version == "3.9"
scipy==1.14.1 ; python_version > "3.9"
# Pin SciPy because of failing distribution tests (see #60347)
#Description: scientific python
#Pinned versions: 1.10.1
#test that import: test_unary_ufuncs.py, test_torch.py,test_tensor_creation_ops.py
#test_spectral_ops.py, test_sparse_csr.py, test_reductions.py,test_nn.py
#test_linalg.py, test_binary_ufuncs.py

#tabulate
#Description: Pretty-print tabular data
#Pinned versions:
#test that import:

# needed by torchgen utils
typing-extensions>=4.10.0
#Description: type hints for python
#Pinned versions:
#test that import:

#virtualenv
#Description: virtual environment for python
#Pinned versions:
#test that import:

unittest-xml-reporting<=3.2.0,>=2.0.0
#Description: saves unit test results to xml
#Pinned versions:
#test that import:

#lintrunner is supported on aarch64-linux only from 0.12.4 version
lintrunner==0.12.7
#Description: all about linters!
#Pinned versions: 0.12.7
#test that import:

redis>=4.0.0
#Description: redis database
#test that import: anything that tests OSS caching/mocking (inductor/test_codecache.py, inductor/test_max_autotune.py)

ghstack==0.8.0
#Description: ghstack tool
#Pinned versions: 0.8.0
#test that import:

jinja2==3.1.6
#Description: jinja2 template engine
#Pinned versions: 3.1.4
#test that import:

pytest-cpp==2.3.0
#Description: This is used by pytest to invoke C++ tests
#Pinned versions: 2.3.0
#test that import:

z3-solver==4.15.1.0 ; platform_machine != "s390x"
#Description: The Z3 Theorem Prover Project
#Pinned versions:
#test that import:

tensorboard==2.18.0
#Description: Also included in .ci/docker/requirements-docs.txt
#Pinned versions:
#test that import: test_tensorboard

pywavelets==1.4.1 ; python_version < "3.12"
pywavelets==1.7.0 ; python_version >= "3.12"
#Description: This is a requirement of scikit-image, we need to pin
# it here because 1.5.0 conflicts with numpy 1.21.2 used in CI
#Pinned versions: 1.4.1
#test that import:

lxml==5.3.0 ; python_version <= "3.12"
lxml==6.0.0 ; python_version == "3.13"
#Description: This is a requirement of unittest-xml-reporting

PyGithub==2.3.0

sympy==1.13.3
#Description: Required by coremltools, also pinned in .github/requirements/pip-requirements-macOS.txt
#Pinned versions:
#test that import:

onnx==1.18.0
#Description: Required by onnx tests, and mypy and test_public_bindings.py when checking torch.onnx._internal

#Pinned versions:
#test that import:

onnxscript==0.4.0
#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
#Pinned versions:
#test that import:

parameterized==0.8.1
#Description: Parameterizes unittests, both the tests themselves and the entire testing class
#Pinned versions:
#test that import:

#Description: required for testing torch/distributed/_tools/sac_estimator.py
#Pinned versions: 1.24.0
#test that import: test_sac_estimator.py

pwlf==2.2.1
#Description: required for testing torch/distributed/_tools/sac_estimator.py
#Pinned versions: 2.2.1
#test that import: test_sac_estimator.py

# To build PyTorch itself
pyyaml
pyzstd
setuptools>=70.1.0
six

scons==4.5.2 ; platform_machine == "aarch64"

pulp==2.9.0
#Description: required for testing ilp formulaiton under torch/distributed/_tools
#Pinned versions: 2.9.0
#test that import: test_sac_ilp.py

dataclasses_json==0.6.7
#Description: required for data pipeline and scripts under tools/stats
#Pinned versions: 0.6.7
#test that import:

cmake==4.0.0
#Description: required for building

tlparse==0.4.0
#Description: required for log parsing

cuda-bindings>=12.0,<13.0 ; platform_machine != "s390x"
#Description: required for testing CUDAGraph::raw_cuda_graph(). See https://nvidia.github.io/cuda-python/cuda-bindings/latest/support.html for how this version was chosen. Note "Any fix in the latest bindings would be backported to the prior major version" means that only the newest version of cuda-bindings will get fixes. Depending on the latest version of 12.x is okay because all 12.y versions will be supported via "CUDA minor version compatibility". Pytorch builds against 13.z versions of cuda toolkit work with 12.x versions of cuda-bindings as well because newer drivers work with old toolkits.
#test that import: test_cuda.py

setuptools-git-versioning==2.1.0
scikit-build==0.18.1
pyre-extensions==0.0.32
tabulate==0.9.0
#Description: These package are needed to build FBGEMM and torchrec on PyTorch CI