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[CI] Fix broken workflows (pytorch#2418)
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vmoens authored Sep 4, 2024
1 parent 60cd104 commit 0326c41
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Showing 4 changed files with 16 additions and 11 deletions.
2 changes: 1 addition & 1 deletion .github/unittest/linux_libs/scripts_minari/environment.yml
Original file line number Diff line number Diff line change
Expand Up @@ -17,4 +17,4 @@ dependencies:
- pyyaml
- scipy
- hydra-core
- minari
- minari[gcs]
7 changes: 5 additions & 2 deletions .github/workflows/build-wheels-windows.yml
Original file line number Diff line number Diff line change
Expand Up @@ -32,6 +32,8 @@ jobs:
matrix:
include:
- repository: pytorch/rl
pre-script: .github/scripts/td_script.sh
env-script: .github/scripts/version_script.bat
post-script: "python packaging/wheel/relocate.py"
smoke-test-script: test/smoke_test.py
package-name: torchrl
Expand All @@ -43,8 +45,9 @@ jobs:
test-infra-repository: pytorch/test-infra
test-infra-ref: main
build-matrix: ${{ needs.generate-matrix.outputs.matrix }}
pre-script: ${{ matrix.pre-script }}
env-script: ${{ matrix.env-script }}
post-script: ${{ matrix.post-script }}
package-name: ${{ matrix.package-name }}
smoke-test-script: ${{ matrix.smoke-test-script }}
trigger-event: ${{ github.event_name }}
pre-script: .github/scripts/td_script.sh
env-script: .github/scripts/version_script.bat
2 changes: 1 addition & 1 deletion .github/workflows/docs.yml
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Expand Up @@ -50,7 +50,7 @@ jobs:
conda activate "${env_dir}"
# 2. upgrade pip, ninja and packaging
apt-get install python3.9 python3-pip -y
# apt-get install python3.9 python3-pip -y
python3 -m pip install --upgrade pip
python3 -m pip install setuptools ninja packaging -U
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16 changes: 9 additions & 7 deletions test/test_loggers.py
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Expand Up @@ -281,25 +281,27 @@ def test_log_video(self, wandb_logger):
# C - number of image channels (e.g. 3 for RGB), H, W - image dimensions.
# the first 64 frames are black and the next 64 are white
video = torch.cat(
(torch.zeros(64, 1, 32, 32), torch.full((64, 1, 32, 32), 255))
(torch.zeros(128, 1, 32, 32), torch.full((128, 1, 32, 32), 255))
)
video = video[None, :]
wandb_logger.log_video(
name="foo",
video=video,
fps=6,
fps=4,
format="mp4",
)
wandb_logger.log_video(
name="foo_12fps",
name="foo_16fps",
video=video,
fps=24,
fps=16,
format="mp4",
)
sleep(0.01) # wait until events are registered

# check that fps can be passed and that it has impact on the length of the video
video_6fps_size = wandb_logger.experiment.summary["foo"]["size"]
video_24fps_size = wandb_logger.experiment.summary["foo_12fps"]["size"]
assert video_6fps_size > video_24fps_size, video_6fps_size
video_4fps_size = wandb_logger.experiment.summary["foo"]["size"]
video_16fps_size = wandb_logger.experiment.summary["foo_16fps"]["size"]
assert video_4fps_size > video_16fps_size, (video_4fps_size, video_16fps_size)

# check that we catch the error in case the format of the tensor is wrong
video_wrong_format = torch.zeros(64, 2, 32, 32)
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