Start migration off defaults to conda-forge channel #4126
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…#4126) Summary: Pull Request resolved: facebookresearch#4126 Differential Revision: D68043874
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Summary: Good resource on overriding channels to make sure we aren't using `defaults`:https://stackoverflow.com/questions/67695893/how-do-i-completely-purge-and-disable-the-default-channel-in-anaconda-and-switch Explanation of changes: - - changed to miniforge from miniconda: this ensures we only pull in from conda-defaults when creating the environment - architecture change: ARM64 and aarch64 are the same thing. But there is no miniforge package for ARM64, so we need to make it check for aarch64 instead. - mkl 2022.2.1 change: conda-forge and defaults have completely different dependencies. Defaults required intel-openmp, but now on conda-forge, mkl 2023.1 or higher requires llvm-openmp >=14.0.6, but this is incompatible with the pytorch build <2.5 which requires llvm-openmp<14.0. We would need to upgrade Python to 3.12 first, upgrade Pytorch build, then upgrade this mkl. (The meta.yaml changes are the ones that narrow it to 2022.2.1 during `conda build faiss`.) So, this has just been changed to 2022.2.1. - mkl now requires _openmp_mutex of type "llvm" instead of "gnu": prior non-cuVS builds all used gnu, because intel-openmp from anaconda defaults channel does not require llvm-openmp. Now we need to remove the gnu one which is automatically pulled in during miniconda setup, and only keep the llvm version of _openmp_mutex. - liblief: The above changes tried to pull in liblief 0.15. This results in an error like `AttributeError: module 'lief._lief.ELF' has no attribute 'ELF_CLASS'`. When I checked passing PR builds on defaults, they use lief 0.12, so I pinned that one. Differential Revision: D68043874
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Summary: Good resource on overriding channels to make sure we aren't using `defaults`:https://stackoverflow.com/questions/67695893/how-do-i-completely-purge-and-disable-the-default-channel-in-anaconda-and-switch Explanation of changes: - - changed to miniforge from miniconda: this ensures we only pull in from conda-defaults when creating the environment - architecture change: ARM64 and aarch64 are the same thing. But there is no miniforge package for ARM64, so we need to make it check for aarch64 instead. - mkl 2022.2.1 change: conda-forge and defaults have completely different dependencies. Defaults required intel-openmp, but now on conda-forge, mkl 2023.1 or higher requires llvm-openmp >=14.0.6, but this is incompatible with the pytorch build <2.5 which requires llvm-openmp<14.0. We would need to upgrade Python to 3.12 first, upgrade Pytorch build, then upgrade this mkl. (The meta.yaml changes are the ones that narrow it to 2022.2.1 during `conda build faiss`.) So, this has just been changed to 2022.2.1. - mkl now requires _openmp_mutex of type "llvm" instead of "gnu": prior non-cuVS builds all used gnu, because intel-openmp from anaconda defaults channel does not require llvm-openmp. Now we need to remove the gnu one which is automatically pulled in during miniconda setup, and only keep the llvm version of _openmp_mutex. - liblief: The above changes tried to pull in liblief 0.15. This results in an error like `AttributeError: module 'lief._lief.ELF' has no attribute 'ELF_CLASS'`. When I checked passing PR builds on defaults, they use lief 0.12, so I pinned that one. Differential Revision: D68043874
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Summary: Good resource on overriding channels to make sure we aren't using `defaults`:https://stackoverflow.com/questions/67695893/how-do-i-completely-purge-and-disable-the-default-channel-in-anaconda-and-switch Explanation of changes: - - changed to miniforge from miniconda: this ensures we only pull in from conda-defaults when creating the environment - architecture change: ARM64 and aarch64 are the same thing. But there is no miniforge package for ARM64, so we need to make it check for aarch64 instead. - mkl 2022.2.1 change: conda-forge and defaults have completely different dependencies. Defaults required intel-openmp, but now on conda-forge, mkl 2023.1 or higher requires llvm-openmp >=14.0.6, but this is incompatible with the pytorch build <2.5 which requires llvm-openmp<14.0. We would need to upgrade Python to 3.12 first, upgrade Pytorch build, then upgrade this mkl. (The meta.yaml changes are the ones that narrow it to 2022.2.1 during `conda build faiss`.) So, this has just been changed to 2022.2.1. - mkl now requires _openmp_mutex of type "llvm" instead of "gnu": prior non-cuVS builds all used gnu, because intel-openmp from anaconda defaults channel does not require llvm-openmp. Now we need to remove the gnu one which is automatically pulled in during miniconda setup, and only keep the llvm version of _openmp_mutex. - liblief: The above changes tried to pull in liblief 0.15. This results in an error like `AttributeError: module 'lief._lief.ELF' has no attribute 'ELF_CLASS'`. When I checked passing PR builds on defaults, they use lief 0.12, so I pinned that one. Differential Revision: D68043874
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Summary: Good resource on overriding channels to make sure we aren't using `defaults`:https://stackoverflow.com/questions/67695893/how-do-i-completely-purge-and-disable-the-default-channel-in-anaconda-and-switch Explanation of changes: - - changed to miniforge from miniconda: this ensures we only pull in from conda-defaults when creating the environment - architecture change: ARM64 and aarch64 are the same thing. But there is no miniforge package for ARM64, so we need to make it check for aarch64 instead. - mkl 2022.2.1 change: conda-forge and defaults have completely different dependencies. Defaults required intel-openmp, but now on conda-forge, mkl 2023.1 or higher requires llvm-openmp >=14.0.6, but this is incompatible with the pytorch build <2.5 which requires llvm-openmp<14.0. We would need to upgrade Python to 3.12 first, upgrade Pytorch build, then upgrade this mkl. (The meta.yaml changes are the ones that narrow it to 2022.2.1 during `conda build faiss`.) So, this has just been changed to 2022.2.1. - mkl now requires _openmp_mutex of type "llvm" instead of "gnu": prior non-cuVS builds all used gnu, because intel-openmp from anaconda defaults channel does not require llvm-openmp. Now we need to remove the gnu one which is automatically pulled in during miniconda setup, and only keep the llvm version of _openmp_mutex. - liblief: The above changes tried to pull in liblief 0.15. This results in an error like `AttributeError: module 'lief._lief.ELF' has no attribute 'ELF_CLASS'`. When I checked passing PR builds on defaults, they use lief 0.12, so I pinned that one. Differential Revision: D68043874
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Summary: Good resource on overriding channels to make sure we aren't using `defaults`:https://stackoverflow.com/questions/67695893/how-do-i-completely-purge-and-disable-the-default-channel-in-anaconda-and-switch Explanation of changes: - - changed to miniforge from miniconda: this ensures we only pull in from conda-defaults when creating the environment - architecture change: ARM64 and aarch64 are the same thing. But there is no miniforge package for ARM64, so we need to make it check for aarch64 instead. - mkl 2022.2.1 change: conda-forge and defaults have completely different dependencies. Defaults required intel-openmp, but now on conda-forge, mkl 2023.1 or higher requires llvm-openmp >=14.0.6, but this is incompatible with the pytorch build <2.5 which requires llvm-openmp<14.0. We would need to upgrade Python to 3.12 first, upgrade Pytorch build, then upgrade this mkl. (The meta.yaml changes are the ones that narrow it to 2022.2.1 during `conda build faiss`.) So, this has just been changed to 2022.2.1. - mkl now requires _openmp_mutex of type "llvm" instead of "gnu": prior non-cuVS builds all used gnu, because intel-openmp from anaconda defaults channel does not require llvm-openmp. Now we need to remove the gnu one which is automatically pulled in during miniconda setup, and only keep the llvm version of _openmp_mutex. - liblief: The above changes tried to pull in liblief 0.15. This results in an error like `AttributeError: module 'lief._lief.ELF' has no attribute 'ELF_CLASS'`. When I checked passing PR builds on defaults, they use lief 0.12, so I pinned that one. Differential Revision: D68043874
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Summary: Good resource on overriding channels to make sure we aren't using `defaults`:https://stackoverflow.com/questions/67695893/how-do-i-completely-purge-and-disable-the-default-channel-in-anaconda-and-switch Explanation of changes: - - changed to miniforge from miniconda: this ensures we only pull in from conda-defaults when creating the environment - architecture change: ARM64 and aarch64 are the same thing. But there is no miniforge package for ARM64, so we need to make it check for aarch64 instead. - mkl 2022.2.1 change: conda-forge and defaults have completely different dependencies. Defaults required intel-openmp, but now on conda-forge, mkl 2023.1 or higher requires llvm-openmp >=14.0.6, but this is incompatible with the pytorch build <2.5 which requires llvm-openmp<14.0. We would need to upgrade Python to 3.12 first, upgrade Pytorch build, then upgrade this mkl. (The meta.yaml changes are the ones that narrow it to 2022.2.1 during `conda build faiss`.) So, this has just been changed to 2022.2.1. - mkl now requires _openmp_mutex of type "llvm" instead of "gnu": prior non-cuVS builds all used gnu, because intel-openmp from anaconda defaults channel does not require llvm-openmp. Now we need to remove the gnu one which is automatically pulled in during miniconda setup, and only keep the llvm version of _openmp_mutex. - liblief: The above changes tried to pull in liblief 0.15. This results in an error like `AttributeError: module 'lief._lief.ELF' has no attribute 'ELF_CLASS'`. When I checked passing PR builds on defaults, they use lief 0.12, so I pinned that one. Differential Revision: D68043874
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Summary: Good resource on overriding channels to make sure we aren't using `defaults`:https://stackoverflow.com/questions/67695893/how-do-i-completely-purge-and-disable-the-default-channel-in-anaconda-and-switch Explanation of changes: - - changed to miniforge from miniconda: this ensures we only pull in from conda-defaults when creating the environment - architecture change: ARM64 and aarch64 are the same thing. But there is no miniforge package for ARM64, so we need to make it check for aarch64 instead. - mkl 2022.2.1 change: conda-forge and defaults have completely different dependencies. Defaults required intel-openmp, but now on conda-forge, mkl 2023.1 or higher requires llvm-openmp >=14.0.6, but this is incompatible with the pytorch build <2.5 which requires llvm-openmp<14.0. We would need to upgrade Python to 3.12 first, upgrade Pytorch build, then upgrade this mkl. (The meta.yaml changes are the ones that narrow it to 2022.2.1 during `conda build faiss`.) So, this has just been changed to 2022.2.1. - mkl now requires _openmp_mutex of type "llvm" instead of "gnu": prior non-cuVS builds all used gnu, because intel-openmp from anaconda defaults channel does not require llvm-openmp. Now we need to remove the gnu one which is automatically pulled in during miniconda setup, and only keep the llvm version of _openmp_mutex. - liblief: The above changes tried to pull in liblief 0.15. This results in an error like `AttributeError: module 'lief._lief.ELF' has no attribute 'ELF_CLASS'`. When I checked passing PR builds on defaults, they use lief 0.12, so I pinned that one. Differential Revision: D68043874
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Summary: Good resource on overriding channels to make sure we aren't using `defaults`:https://stackoverflow.com/questions/67695893/how-do-i-completely-purge-and-disable-the-default-channel-in-anaconda-and-switch Explanation of changes: - - changed to miniforge from miniconda: this ensures we only pull in from conda-defaults when creating the environment - architecture change: ARM64 and aarch64 are the same thing. But there is no miniforge package for ARM64, so we need to make it check for aarch64 instead. - mkl 2022.2.1 change: conda-forge and defaults have completely different dependencies. Defaults required intel-openmp, but now on conda-forge, mkl 2023.1 or higher requires llvm-openmp >=14.0.6, but this is incompatible with the pytorch build <2.5 which requires llvm-openmp<14.0. We would need to upgrade Python to 3.12 first, upgrade Pytorch build, then upgrade this mkl. (The meta.yaml changes are the ones that narrow it to 2022.2.1 during `conda build faiss`.) So, this has just been changed to 2022.2.1. - mkl now requires _openmp_mutex of type "llvm" instead of "gnu": prior non-cuVS builds all used gnu, because intel-openmp from anaconda defaults channel does not require llvm-openmp. Now we need to remove the gnu one which is automatically pulled in during miniconda setup, and only keep the llvm version of _openmp_mutex. - liblief: The above changes tried to pull in liblief 0.15. This results in an error like `AttributeError: module 'lief._lief.ELF' has no attribute 'ELF_CLASS'`. When I checked passing PR builds on defaults, they use lief 0.12, so I pinned that one. Differential Revision: D68043874
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Summary: Good resource on overriding channels to make sure we aren't using `defaults`:https://stackoverflow.com/questions/67695893/how-do-i-completely-purge-and-disable-the-default-channel-in-anaconda-and-switch Explanation of changes: - - changed to miniforge from miniconda: this ensures we only pull in from conda-defaults when creating the environment - architecture change: ARM64 and aarch64 are the same thing. But there is no miniforge package for ARM64, so we need to make it check for aarch64 instead. - mkl 2022.2.1 change: conda-forge and defaults have completely different dependencies. Defaults required intel-openmp, but now on conda-forge, mkl 2023.1 or higher requires llvm-openmp >=14.0.6, but this is incompatible with the pytorch build <2.5 which requires llvm-openmp<14.0. We would need to upgrade Python to 3.12 first, upgrade Pytorch build, then upgrade this mkl. (The meta.yaml changes are the ones that narrow it to 2022.2.1 during `conda build faiss`.) So, this has just been changed to 2022.2.1. - mkl now requires _openmp_mutex of type "llvm" instead of "gnu": prior non-cuVS builds all used gnu, because intel-openmp from anaconda defaults channel does not require llvm-openmp. Now we need to remove the gnu one which is automatically pulled in during miniconda setup, and only keep the llvm version of _openmp_mutex. - liblief: The above changes tried to pull in liblief 0.15. This results in an error like `AttributeError: module 'lief._lief.ELF' has no attribute 'ELF_CLASS'`. When I checked passing PR builds on defaults, they use lief 0.12, so I pinned that one. Differential Revision: D68043874
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Summary: Good resource on overriding channels to make sure we aren't using `defaults`:https://stackoverflow.com/questions/67695893/how-do-i-completely-purge-and-disable-the-default-channel-in-anaconda-and-switch Explanation of changes: - - changed to miniforge from miniconda: this ensures we only pull in from conda-defaults when creating the environment - architecture change: ARM64 and aarch64 are the same thing. But there is no miniforge package for ARM64, so we need to make it check for aarch64 instead. - mkl 2022.2.1 change: conda-forge and defaults have completely different dependencies. Defaults required intel-openmp, but now on conda-forge, mkl 2023.1 or higher requires llvm-openmp >=14.0.6, but this is incompatible with the pytorch build <2.5 which requires llvm-openmp<14.0. We would need to upgrade Python to 3.12 first, upgrade Pytorch build, then upgrade this mkl. (The meta.yaml changes are the ones that narrow it to 2022.2.1 during `conda build faiss`.) So, this has just been changed to 2022.2.1. - mkl now requires _openmp_mutex of type "llvm" instead of "gnu": prior non-cuVS builds all used gnu, because intel-openmp from anaconda defaults channel does not require llvm-openmp. Now we need to remove the gnu one which is automatically pulled in during miniconda setup, and only keep the llvm version of _openmp_mutex. - liblief: The above changes tried to pull in liblief 0.15. This results in an error like `AttributeError: module 'lief._lief.ELF' has no attribute 'ELF_CLASS'`. When I checked passing PR builds on defaults, they use lief 0.12, so I pinned that one. Differential Revision: D68043874
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Differential Revision: D68043874