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Code Issues Projects Releases Wiki Activity

[Improvement] Add more CI (#460)

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* add more CI

* fix missing

* remove python-version

* fixed acc
This commit is contained in:
Jerry Jiarui XU 2021-04-08 19:29:00 -07:00 committed by GitHub
parent 99ab9bd2d9
commit d283ca6fea
3 changed files with 1110 additions and 1109 deletions
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19
.github/workflows/build.yml vendored
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@ -29,25 +29,26 @@ jobs:
UBUNTU_VERSION: ubuntu1804 UBUNTU_VERSION: ubuntu1804
FORCE_CUDA: 1 FORCE_CUDA: 1
MMCV_CUDA_ARGS: -gencode=arch=compute_61,code=sm_61 MMCV_CUDA_ARGS: -gencode=arch=compute_61,code=sm_61
runs-on: ubuntu-latest runs-on: ubuntu-18.04
strategy: strategy:
matrix: matrix:
python-version: [ 3.6, 3.7 ] python-version: [ 3.6, 3.7 ]
torch: [1.3.0+cpu, 1.5.0+cpu] torch: [ 1.3.0+cpu, 1.5.0+cpu, 1.5.0+cu101, 1.6.0+cu101, 1.7.0+cu101, 1.8.0+cu101 ]
include: include:
- torch: 1.3.0+cpu - torch: 1.3.0+cpu
torchvision: 0.4.1+cpu torchvision: 0.4.1+cpu
- torch: 1.5.0+cpu - torch: 1.5.0+cpu
torchvision: 0.6.0+cpu torchvision: 0.6.0+cpu
- torch: 1.5.0+cpu
torchvision: 0.6.0+cpu
python-version: 3.8
- torch: 1.5.0+cu101 - torch: 1.5.0+cu101
torchvision: 0.6.0+cu101 torchvision: 0.6.0+cu101
python-version: 3.7
- torch: 1.6.0+cu101 - torch: 1.6.0+cu101
torchvision: 0.7.0+cu101 torchvision: 0.7.0+cu101
python-version: 3.7 - torch: 1.7.0+cu101
torchvision: 0.8.1+cu101
- torch: 1.8.0+cu101
torchvision: 0.9.0+cu101
- torch: 1.8.0+cu101
torchvision: 0.9.0+cu101
steps: steps:
- uses: actions/checkout@v2 - uses: actions/checkout@v2
@ -56,7 +57,7 @@ jobs:
with: with:
python-version: ${{ matrix.python-version }} python-version: ${{ matrix.python-version }}
- name: Install CUDA - name: Install CUDA
if: ${{matrix.torch == '1.5.0+cu101'}} if: ${{matrix.torch == '1.5.0+cu101' || matrix.torch == '1.6.0+cu101' || matrix.torch == '1.7.0+cu101' || matrix.torch == '1.8.0+cu101'}}
run: | run: |
export INSTALLER=cuda-repo-${UBUNTU_VERSION}_${CUDA}_amd64.deb export INSTALLER=cuda-repo-${UBUNTU_VERSION}_${CUDA}_amd64.deb
wget http://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/${INSTALLER} wget http://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/${INSTALLER}
@ -88,7 +89,7 @@ jobs:
coverage report -m coverage report -m
# Only upload coverage report for python3.7 && pytorch1.5 # Only upload coverage report for python3.7 && pytorch1.5
- name: Upload coverage to Codecov - name: Upload coverage to Codecov
if: ${{matrix.torch == '1.5.0+cu101' && matrix.python-version == '3.7'}} if: ${{matrix.torch == '1.8.0+cu101' && matrix.python-version == '3.7'}}
uses: codecov/codecov-action@v1.0.10 uses: codecov/codecov-action@v1.0.10
with: with:
file: ./coverage.xml file: ./coverage.xml

8
demo/MMSegmentation_Tutorial.ipynb
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@ -161,10 +161,10 @@
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"Cloning into 'mmsegmentation'...\n", "Cloning into 'mmsegmentation'...\n",
"remote: Enumerating objects: 64, done.\u001b[K\n", "remote: Enumerating objects: 64, done.\u001B[K\n",
"remote: Counting objects: 100% (64/64), done.\u001b[K\n", "remote: Counting objects: 100% (64/64), done.\u001B[K\n",
"remote: Compressing objects: 100% (60/60), done.\u001b[K\n", "remote: Compressing objects: 100% (60/60), done.\u001B[K\n",
"remote: Total 2194 (delta 17), reused 12 (delta 4), pack-reused 2130\u001b[K\n", "remote: Total 2194 (delta 17), reused 12 (delta 4), pack-reused 2130\u001B[K\n",
"Receiving objects: 100% (2194/2194), 3.35 MiB | 26.82 MiB/s, done.\n", "Receiving objects: 100% (2194/2194), 3.35 MiB | 26.82 MiB/s, done.\n",
"Resolving deltas: 100% (1536/1536), done.\n", "Resolving deltas: 100% (1536/1536), done.\n",
"/content/mmsegmentation\n", "/content/mmsegmentation\n",

2
mmseg/models/losses/accuracy.py
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@ -44,7 +44,7 @@ def accuracy(pred, target, topk=1, thresh=None):
correct = correct & (pred_value > thresh).t() correct = correct & (pred_value > thresh).t()
res = [] res = []
for k in topk: for k in topk:
correct_k = correct[:k].view(-1).float().sum(0, keepdim=True) correct_k = correct[:k].reshape(-1).float().sum(0, keepdim=True)
res.append(correct_k.mul_(100.0 / target.numel())) res.append(correct_k.mul_(100.0 / target.numel()))
return res[0] if return_single else res return res[0] if return_single else res