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adding easyconfigs: PyTorch-2.1.2-foss-2022b-CUDA-12.0.0.eb and patch…
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…es: PyTorch-2.1.2_add-cuda-skip-markers.patch, PyTorch-2.1.2_fix-conj-mismatch-test-failures.patch, PyTorch-2.1.2_fix-device-mesh-check.patch, PyTorch-2.1.2_fix-locale-issue-in-nvrtcCompileProgram.patch, PyTorch-2.1.2_fix-test_extension_backend-without-vectorization.patch, PyTorch-2.1.2_fix-test_memory_profiler.patch, PyTorch-2.1.2_fix-test_torchinductor-rounding.patch, PyTorch-2.1.2_fix-vsx-vector-abs.patch, PyTorch-2.1.2_fix-vsx-vector-div.patch, PyTorch-2.1.2_fix-with_temp_dir-decorator.patch, PyTorch-2.1.2_fix-wrong-device-mesh-size-in-tests.patch, PyTorch-2.1.2_relax-cuda-tolerances.patch, PyTorch-2.1.2_remove-nccl-backend-default-without-gpus.patch, PyTorch-2.1.2_skip-cpu_repro-test-without-vectorization.patch, PyTorch-2.1.2_skip-failing-test_dtensor_ops-subtests.patch, PyTorch-2.1.2_skip-test_fsdp_tp_checkpoint_integration.patch, PyTorch-2.1.2_workaround_dynamo_failure_without_nnpack.patch
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Flamefire committed Apr 16, 2024
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name = 'PyTorch'
version = '2.1.2'
versionsuffix = '-CUDA-%(cudaver)s'

homepage = 'https://pytorch.org/'
description = """Tensors and Dynamic neural networks in Python with strong GPU acceleration.
PyTorch is a deep learning framework that puts Python first."""

toolchain = {'name': 'foss', 'version': '2022b'}

source_urls = [GITHUB_RELEASE]
sources = ['%(namelower)s-v%(version)s.tar.gz']
patches = [
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'PyTorch-1.12.1_fix-test_cpp_extensions_jit.patch',
'PyTorch-1.12.1_fix-TestTorch.test_to.patch',
'PyTorch-1.12.1_skip-test_round_robin.patch',
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'PyTorch-1.13.1_skip-failing-singular-grad-test.patch',
'PyTorch-1.13.1_skip-tests-without-fbgemm.patch',
'PyTorch-2.0.1_avoid-test_quantization-failures.patch',
'PyTorch-2.0.1_fix-skip-decorators.patch',
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'PyTorch-2.1.0_disable-gcc12-warning.patch',
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'PyTorch-2.1.0_fix-test_numpy_torch_operators.patch',
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'PyTorch-2.1.0_skip-diff-test-on-ppc.patch',
'PyTorch-2.1.0_skip-dynamo-test_predispatch.patch',
'PyTorch-2.1.0_skip-test_jvp_linalg_det_singular.patch',
'PyTorch-2.1.0_skip-test_linear_fp32-without-MKL.patch',
'PyTorch-2.1.0_skip-test_wrap_bad.patch',
'PyTorch-2.1.2_add-cuda-skip-markers.patch',
'PyTorch-2.1.2_fix-conj-mismatch-test-failures.patch',
'PyTorch-2.1.2_fix-device-mesh-check.patch',
'PyTorch-2.1.2_fix-locale-issue-in-nvrtcCompileProgram.patch',
'PyTorch-2.1.2_fix-test_extension_backend-without-vectorization.patch',
'PyTorch-2.1.2_fix-test_memory_profiler.patch',
'PyTorch-2.1.2_fix-test_torchinductor-rounding.patch',
'PyTorch-2.1.2_fix-vsx-vector-abs.patch',
'PyTorch-2.1.2_fix-vsx-vector-div.patch',
'PyTorch-2.1.2_fix-with_temp_dir-decorator.patch',
'PyTorch-2.1.2_fix-wrong-device-mesh-size-in-tests.patch',
'PyTorch-2.1.2_relax-cuda-tolerances.patch',
'PyTorch-2.1.2_remove-nccl-backend-default-without-gpus.patch',
'PyTorch-2.1.2_skip-cpu_repro-test-without-vectorization.patch',
'PyTorch-2.1.2_skip-failing-test_dtensor_ops-subtests.patch',
'PyTorch-2.1.2_skip-test_fsdp_tp_checkpoint_integration.patch',
'PyTorch-2.1.2_workaround_dynamo_failure_without_nnpack.patch',
]
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osdependencies = [OS_PKG_IBVERBS_DEV]

builddependencies = [
('CMake', '3.24.3'),
('hypothesis', '6.68.2'),
# For tests
('pytest-flakefinder', '1.1.0'),
('pytest-rerunfailures', '12.0'),
('pytest-shard', '0.1.2'),
]

dependencies = [
('CUDA', '12.0.0', '', SYSTEM),
('cuDNN', '8.8.0.121', '-CUDA-%(cudaver)s', SYSTEM),
('magma', '2.7.1', '-CUDA-%(cudaver)s'),
('NCCL', '2.16.2', '-CUDA-%(cudaver)s'),
('Ninja', '1.11.1'), # Required for JIT compilation of C++ extensions
('Python', '3.10.8'),
('protobuf', '23.0'),
('protobuf-python', '4.23.0'),
('pybind11', '2.10.3'),
('SciPy-bundle', '2023.02'),
('PyYAML', '6.0'),
('MPFR', '4.2.0'),
('GMP', '6.2.1'),
('numactl', '2.0.16'),
('FFmpeg', '5.1.2'),
('Pillow', '9.4.0'),
('expecttest', '0.1.3'),
('networkx', '3.0'),
('sympy', '1.12'),
('Z3', '4.12.2', '-Python-%(pyver)s'),
]

use_pip = True
buildcmd = '%(python)s setup.py build' # Run the (long) build in the build step

excluded_tests = {
'': [
# This test seems to take too long on NVIDIA Ampere at least.
'distributed/test_distributed_spawn',
# Broken on CUDA 11.6/11.7: https://github.com/pytorch/pytorch/issues/75375
'distributions/test_constraints',
# no xdoctest
'doctests',
# failing on broadwell
# See https://github.com/easybuilders/easybuild-easyconfigs/issues/17712
'test_native_mha',
# intermittent failures on various systems
# See https://github.com/easybuilders/easybuild-easyconfigs/issues/17712
'distributed/rpc/test_tensorpipe_agent',
# Broken test, can't ever succeed, see https://github.com/pytorch/pytorch/issues/122184
'distributed/tensor/parallel/test_tp_random_state',
# failures on OmniPath systems, which don't support some optional InfiniBand features
# See https://github.com/pytorch/tensorpipe/issues/413
'distributed/pipeline/sync/skip/test_gpipe',
'distributed/pipeline/sync/skip/test_leak',
'distributed/pipeline/sync/test_bugs',
'distributed/pipeline/sync/test_inplace',
'distributed/pipeline/sync/test_pipe',
'distributed/pipeline/sync/test_transparency',
]
}

runtest = 'cd test && PYTHONUNBUFFERED=1 %(python)s run_test.py --continue-through-error --verbose %(excluded_tests)s'

# Especially test_quantization has a few corner cases that are triggered by the random input values,
# those cannot be easily avoided, see https://github.com/pytorch/pytorch/issues/107030
# test_nn is also prone to spurious failures: https://github.com/pytorch/pytorch/issues/118294
# So allow a low number of tests to fail as the tests "usually" succeed
max_failed_tests = 10

# The readelf sanity check command can be taken out once the TestRPATH test from
# https://github.com/pytorch/pytorch/pull/109493 is accepted, since it is then checked as part of the PyTorch test suite
local_libcaffe2 = "$EBROOTPYTORCH/lib/python%%(pyshortver)s/site-packages/torch/lib/libcaffe2_nvrtc.%s" % SHLIB_EXT
sanity_check_commands = [
"readelf -d %s | egrep 'RPATH|RUNPATH' | grep -v stubs" % local_libcaffe2,
]

tests = ['PyTorch-check-cpp-extension.py']

moduleclass = 'ai'

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