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Remove "track_features" from cpuonly
conda package
#823
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c5d0396
Add pytorch-mutex metapackage to choose PyTorch build variant
IvanYashchuk 39eac88
Use run_constrained with cpuonly
IvanYashchuk c93f858
Fix missing \ and remove OVERRIDE_PACKAGE_VERSION
IvanYashchuk 6bdd93c
Merge branch 'master' into pytorch-mutex
IvanYashchuk 570b7ca
Restore track_features in cpuonly/meta.yaml
IvanYashchuk a3909be
Merge branch 'main' into pytorch-mutex
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Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -1,8 +1,12 @@ | ||
package: | ||
name: cpuonly | ||
version: 1.0 | ||
version: 2.0 | ||
|
||
build: | ||
track_features: | ||
- cpuonly | ||
noarch: generic | ||
|
||
requirements: | ||
run: | ||
- pytorch-mutex 1.0 cpu | ||
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Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,3 @@ | ||
build_variant: | ||
- cpu | ||
- cuda |
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Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,29 @@ | ||
{% set version = "1.0" %} | ||
{% set build = 0 %} | ||
|
||
{% if build_variant == 'cuda' %} | ||
# prefer cuda builds via a build number offset | ||
{% set build = build + 100 %} | ||
{% endif %} | ||
|
||
package: | ||
name: pytorch-mutex | ||
version: {{ version }} | ||
build: | ||
number: {{ build }} | ||
string: {{ build_variant }} | ||
noarch: generic | ||
# also lower cpu priority with track_features | ||
{% if build_variant == 'cpu' %} | ||
track_features: | ||
- pytorch-mutex | ||
{% endif %} | ||
run_exports: | ||
- {{ pin_subpackage('pytorch-mutex', exact=True) }} | ||
requirements: {} | ||
# None, pytorch should depend on pytorch-mutex | ||
test: | ||
commands: | ||
- echo "pytorch-mutex metapackage is created." | ||
about: | ||
summary: Metapackage to select the PyTorch variant. Use conda's pinning mechanism in your environment to control which variant you want. |
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An alternative option to
pytorch-mutex 1.0 cpu
is to usepytorch=*=*cpu*
. However, runningprefers the main channel
So I think using
pytorch=*=*cpu*
forcpuonly
package could break conda.mamba
chooses the pytorch channel