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Merge pull request #83 from hmaarrfk/0.16.1
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Update to 0.16.1, Pytorch 2.1
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hmaarrfk authored Nov 27, 2023
2 parents ab7b3e6 + c4cf770 commit 43854d5
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32 changes: 16 additions & 16 deletions .azure-pipelines/azure-pipelines-linux.yml

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6 changes: 3 additions & 3 deletions .scripts/build_steps.sh

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6 changes: 3 additions & 3 deletions .scripts/run_osx_build.sh

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34 changes: 17 additions & 17 deletions README.md

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7 changes: 6 additions & 1 deletion recipe/build-torch.sh
Original file line number Diff line number Diff line change
@@ -1,3 +1,5 @@
set -ex

if [[ "$cuda_compiler_version" == "None" ]]; then
export FORCE_CUDA=0
else
Expand All @@ -23,7 +25,10 @@ else
fi

# remove pyproject.toml
rm $SRC_DIR/pyproject.toml
rm -f pyproject.toml

# hmaarrfk I found that it was pretty buggy:
# https://github.com/conda-forge/torchvision-feedstock/pull/60
export TORCHVISION_USE_FFMPEG=0
export TORCHVISION_INCLUDE="${PREFIX}/include/"
${PYTHON} -m pip install . -vv --no-deps --no-build-isolation
8 changes: 4 additions & 4 deletions recipe/meta.yaml
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@@ -1,24 +1,24 @@
{% set version = "0.15.2" %}
{% set version = "0.16.1" %}
# see github.com/conda-forge/conda-forge.github.io/issues/1059 for naming discussion
# torchvision requires that CUDA major and minor versions match with pytorch
# https://github.com/pytorch/vision/blob/fa99a5360fbcd1683311d57a76fcc0e7323a4c1e/torchvision/extension.py#L79C1-L85C1
{% set torch_proc_type = "cuda" ~ cuda_compiler_version | replace('.', '') if cuda_compiler_version != "None" else "cpu" %}
# Upstream has specific compatability ranges for pytorch and python which are
# updated every 0.x release. https://github.com/pytorch/vision#installation
{% set compatible_pytorch = "2.0" %}
{% set compatible_pytorch = "2.1" %}

package:
name: torchvision-split
version: {{ version }}

source:
url: https://github.com/pytorch/vision/archive/v{{ version }}.tar.gz
sha256: 1efcb80e0a6e42c54f07ee16167839b4d302aeeecc12839cc47c74b06a2c20d4
sha256: d31fe52e4540750c8d372b0f38f1bfa81d8261193f2c2c06577332831d203c50
patches:
- 0001-Monkeypatch-TORCH_LIB_PATH.patch

build:
number: 4
number: 0
skip: true # [win]
# as of pytorch 1.13, conda-forge only builds for CUDA 11.2+, see
# https://github.com/conda-forge/conda-forge-pinning-feedstock/issues/3491
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