remove PyTorch 1.5 builds

Summary: PyTorch 1.6.0 came out on 28 Jul 2020. Stop builds for 1.5.0 and 1.5.1. Also update the news section of the README for recent releases.

Reviewed By: nikhilaravi

Differential Revision: D31442830

fbshipit-source-id: 20bdd8a07090776d0461240e71c6536d874615f6
This commit is contained in:
Jeremy Reizenstein 2021-10-11 06:12:06 -07:00 committed by Facebook GitHub Bot
parent 6d36c1e2b0
commit 53d99671bd
9 changed files with 8 additions and 140 deletions

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@ -231,12 +231,6 @@ workflows:
- main: - main:
context: DOCKERHUB_TOKEN context: DOCKERHUB_TOKEN
{{workflows()}} {{workflows()}}
- binary_linux_conda_cuda:
name: testrun_conda_cuda_py36_cu101_pyt151
context: DOCKERHUB_TOKEN
python_version: "3.6"
pytorch_version: "1.5.1"
cu_version: "cu101"
- binary_linux_conda_cuda: - binary_linux_conda_cuda:
name: testrun_conda_cuda_py37_cu102_pyt190 name: testrun_conda_cuda_py37_cu102_pyt190
context: DOCKERHUB_TOKEN context: DOCKERHUB_TOKEN

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@ -230,42 +230,6 @@ workflows:
jobs: jobs:
- main: - main:
context: DOCKERHUB_TOKEN context: DOCKERHUB_TOKEN
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu92
name: linux_conda_py36_cu92_pyt150
python_version: '3.6'
pytorch_version: 1.5.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu101
name: linux_conda_py36_cu101_pyt150
python_version: '3.6'
pytorch_version: 1.5.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py36_cu102_pyt150
python_version: '3.6'
pytorch_version: 1.5.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu92
name: linux_conda_py36_cu92_pyt151
python_version: '3.6'
pytorch_version: 1.5.1
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu101
name: linux_conda_py36_cu101_pyt151
python_version: '3.6'
pytorch_version: 1.5.1
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py36_cu102_pyt151
python_version: '3.6'
pytorch_version: 1.5.1
- binary_linux_conda: - binary_linux_conda:
context: DOCKERHUB_TOKEN context: DOCKERHUB_TOKEN
cu_version: cu92 cu_version: cu92
@ -380,42 +344,6 @@ workflows:
name: linux_conda_py36_cu111_pyt191 name: linux_conda_py36_cu111_pyt191
python_version: '3.6' python_version: '3.6'
pytorch_version: 1.9.1 pytorch_version: 1.9.1
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu92
name: linux_conda_py37_cu92_pyt150
python_version: '3.7'
pytorch_version: 1.5.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu101
name: linux_conda_py37_cu101_pyt150
python_version: '3.7'
pytorch_version: 1.5.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py37_cu102_pyt150
python_version: '3.7'
pytorch_version: 1.5.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu92
name: linux_conda_py37_cu92_pyt151
python_version: '3.7'
pytorch_version: 1.5.1
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu101
name: linux_conda_py37_cu101_pyt151
python_version: '3.7'
pytorch_version: 1.5.1
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py37_cu102_pyt151
python_version: '3.7'
pytorch_version: 1.5.1
- binary_linux_conda: - binary_linux_conda:
context: DOCKERHUB_TOKEN context: DOCKERHUB_TOKEN
cu_version: cu92 cu_version: cu92
@ -530,42 +458,6 @@ workflows:
name: linux_conda_py37_cu111_pyt191 name: linux_conda_py37_cu111_pyt191
python_version: '3.7' python_version: '3.7'
pytorch_version: 1.9.1 pytorch_version: 1.9.1
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu92
name: linux_conda_py38_cu92_pyt150
python_version: '3.8'
pytorch_version: 1.5.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu101
name: linux_conda_py38_cu101_pyt150
python_version: '3.8'
pytorch_version: 1.5.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py38_cu102_pyt150
python_version: '3.8'
pytorch_version: 1.5.0
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu92
name: linux_conda_py38_cu92_pyt151
python_version: '3.8'
pytorch_version: 1.5.1
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu101
name: linux_conda_py38_cu101_pyt151
python_version: '3.8'
pytorch_version: 1.5.1
- binary_linux_conda:
context: DOCKERHUB_TOKEN
cu_version: cu102
name: linux_conda_py38_cu102_pyt151
python_version: '3.8'
pytorch_version: 1.5.1
- binary_linux_conda: - binary_linux_conda:
context: DOCKERHUB_TOKEN context: DOCKERHUB_TOKEN
cu_version: cu92 cu_version: cu92
@ -758,12 +650,6 @@ workflows:
name: linux_conda_py39_cu111_pyt191 name: linux_conda_py39_cu111_pyt191
python_version: '3.9' python_version: '3.9'
pytorch_version: 1.9.1 pytorch_version: 1.9.1
- binary_linux_conda_cuda:
name: testrun_conda_cuda_py36_cu101_pyt151
context: DOCKERHUB_TOKEN
python_version: "3.6"
pytorch_version: "1.5.1"
cu_version: "cu101"
- binary_linux_conda_cuda: - binary_linux_conda_cuda:
name: testrun_conda_cuda_py37_cu102_pyt190 name: testrun_conda_cuda_py37_cu102_pyt190
context: DOCKERHUB_TOKEN context: DOCKERHUB_TOKEN

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@ -19,8 +19,6 @@ import yaml
# version of pytorch. # version of pytorch.
# Pytorch 1.4 also supports cuda 10.0 but we no longer build for cuda 10.0 at all. # Pytorch 1.4 also supports cuda 10.0 but we no longer build for cuda 10.0 at all.
CONDA_CUDA_VERSIONS = { CONDA_CUDA_VERSIONS = {
"1.5.0": ["cu92", "cu101", "cu102"],
"1.5.1": ["cu92", "cu101", "cu102"],
"1.6.0": ["cu92", "cu101", "cu102"], "1.6.0": ["cu92", "cu101", "cu102"],
"1.7.0": ["cu101", "cu102", "cu110"], "1.7.0": ["cu101", "cu102", "cu110"],
"1.7.1": ["cu101", "cu102", "cu110"], "1.7.1": ["cu101", "cu102", "cu110"],

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@ -9,7 +9,7 @@ The core library is written in PyTorch. Several components have underlying imple
- Linux or macOS or Windows - Linux or macOS or Windows
- Python 3.6, 3.7, 3.8 or 3.9 - Python 3.6, 3.7, 3.8 or 3.9
- PyTorch 1.5.0, 1.5.1, 1.6.0, 1.7.0, 1.7.1, 1.8.0, 1.8.1, 1.9.0 or 1.9.1. - PyTorch 1.6.0, 1.7.0, 1.7.1, 1.8.0, 1.8.1, 1.9.0 or 1.9.1.
- torchvision that matches the PyTorch installation. You can install them together as explained at pytorch.org to make sure of this. - torchvision that matches the PyTorch installation. You can install them together as explained at pytorch.org to make sure of this.
- gcc & g++ ≥ 4.9 - gcc & g++ ≥ 4.9
- [fvcore](https://github.com/facebookresearch/fvcore) - [fvcore](https://github.com/facebookresearch/fvcore)

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@ -136,6 +136,10 @@ If you are using the pulsar backend for sphere-rendering (the `PulsarPointRender
Please see below for a timeline of the codebase updates in reverse chronological order. We are sharing updates on the releases as well as research projects which are built with PyTorch3D. The changelogs for the releases are available under [`Releases`](https://github.com/facebookresearch/pytorch3d/releases), and the builds can be installed using `conda` as per the instructions in [INSTALL.md](INSTALL.md). Please see below for a timeline of the codebase updates in reverse chronological order. We are sharing updates on the releases as well as research projects which are built with PyTorch3D. The changelogs for the releases are available under [`Releases`](https://github.com/facebookresearch/pytorch3d/releases), and the builds can be installed using `conda` as per the instructions in [INSTALL.md](INSTALL.md).
**[Oct 6th 2021]:** PyTorch3D [v0.6.0](https://github.com/facebookresearch/pytorch3d/releases/tag/v0.6.0) released
**[Aug 5th 2021]:** PyTorch3D [v0.5.0](https://github.com/facebookresearch/pytorch3d/releases/tag/v0.5.0) released
**[Feb 9th 2021]:** PyTorch3D [v0.4.0](https://github.com/facebookresearch/pytorch3d/releases/tag/v0.4.0) released with support for implicit functions, volume rendering and a [reimplementation of NeRF](https://github.com/facebookresearch/pytorch3d/tree/main/projects/nerf). **[Feb 9th 2021]:** PyTorch3D [v0.4.0](https://github.com/facebookresearch/pytorch3d/releases/tag/v0.4.0) released with support for implicit functions, volume rendering and a [reimplementation of NeRF](https://github.com/facebookresearch/pytorch3d/tree/main/projects/nerf).
**[November 2nd 2020]:** PyTorch3D [v0.3.0](https://github.com/facebookresearch/pytorch3d/releases/tag/v0.3.0) released, integrating the pulsar backend. **[November 2nd 2020]:** PyTorch3D [v0.3.0](https://github.com/facebookresearch/pytorch3d/releases/tag/v0.3.0) released, integrating the pulsar backend.

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@ -53,12 +53,7 @@ do
continue continue
fi fi
if [[ "3.9" == "$python_version" ]] extra_channel="-c conda-forge"
then
extra_channel="-c conda-forge"
else
extra_channel=""
fi
for cu_version in ${CONDA_CUDA_VERSIONS[$pytorch_version]} for cu_version in ${CONDA_CUDA_VERSIONS[$pytorch_version]}
do do

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@ -69,12 +69,7 @@ class HarmonicEmbedding(torch.nn.Module):
dtype=torch.float32, dtype=torch.float32,
) )
try: self.register_buffer("_frequencies", omega0 * frequencies, persistent=False)
self.register_buffer("_frequencies", omega0 * frequencies, persistent=False)
except TypeError:
# workaround for pytorch<1.6
self.register_buffer("_frequencies", omega0 * frequencies)
self.include_input = include_input self.include_input = include_input
def forward(self, x: torch.Tensor) -> torch.Tensor: def forward(self, x: torch.Tensor) -> torch.Tensor:

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@ -96,10 +96,7 @@ class GridRaysampler(torch.nn.Module):
), ),
dim=-1, dim=-1,
) )
try: self.register_buffer("_xy_grid", _xy_grid, persistent=False)
self.register_buffer("_xy_grid", _xy_grid, persistent=False)
except TypeError:
self.register_buffer("_xy_grid", _xy_grid) # workaround for pytorch<1.6
def forward(self, cameras: CamerasBase, **kwargs) -> RayBundle: def forward(self, cameras: CamerasBase, **kwargs) -> RayBundle:
""" """

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@ -12,7 +12,6 @@ from common_testing import TestCaseMixin
from pytorch3d.renderer.implicit.sample_pdf import sample_pdf, sample_pdf_python from pytorch3d.renderer.implicit.sample_pdf import sample_pdf, sample_pdf_python
@unittest.skipIf(torch.__version__[:4] == "1.5.", "searchsorted needs PyTorch 1.6")
class TestSamplePDF(TestCaseMixin, unittest.TestCase): class TestSamplePDF(TestCaseMixin, unittest.TestCase):
def setUp(self) -> None: def setUp(self) -> None:
super().setUp() super().setUp()