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new file: p/PyTorch/PyTorch-1.11.0-foss-2021a-CUDA-11.3.1.eb modified: p/PyTorch/PyTorch-1.11.0-fosscuda-2020b.eb new file: p/PyTorch/PyTorch-1.11.0_disable_failing_jit_cuda_fuser_tests.patch new file: p/PyTorch/PyTorch-1.11.0_fix_sharded_imports.patch new file: p/PyTorch/PyTorch-1.11.0_fix_skip_jit_cuda_fuser.patch new file: p/PyTorch/PyTorch-1.11.0_increase-distributed-test-timeout.patch new file: p/PyTorch/PyTorch-1.11.0_increase_c10d_gloo_timeout.patch new file: p/PyTorch/PyTorch-1.11.0_increase_test_tolerances_TF32.patch new file: p/PyTorch/PyTorch-1.11.0_skip_failing_ops_tests.patch
25 lines
829 B
Plaintext
25 lines
829 B
Plaintext
# IT4Innovations
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# JK 2022
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easyblock = 'PackedBinary'
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name = 'HyperQueue'
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version = '0.10.0'
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homepage = 'https://it4innovations.github.io/hyperqueue/'
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description = """HyperQueue lets you build a computation plan consisting of a large amount of tasks and then execute it transparently over a system like SLURM/PBS. It dynamically groups jobs into SLURM/PBS jobs and distributes them to fully utilize allocated notes. You thus do not have to manually aggregate your tasks into SLURM/PBS jobs."""
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toolchain = SYSTEM
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source_urls = ['https://github.com/It4innovations/hyperqueue/releases/download/v%(version)s/']
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sources = ['hq-v%(version)s-linux-x64.tar.gz']
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checksums = ['2513d5ce7e8b31ace17f5054058c3fed7900ef61e3aa0f27d66f794533cd152c']
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sanity_check_paths = {
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'files': ['hq'],
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'dirs': [],
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}
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moduleclass = 'devel'
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