DGL multi-gpu examples fails on single GPU, 4 GPUs, 8GPUs.
For num_gpus=0, no stderr is returned.
for num_gpus=4, it crashed with below error:
<span class="awsui_body-cell-content_c6tup_98ns9_121"><span class=""><div data-testid="logs__log-events-table__formatted-message"> Training in benchmark mode using 4 GPU(s)</div><div class="logs__copy-button"><span data-analytics="copy-button" data-analytics-type="eventDetail" class="awsui_root_5a145_13ep8_9 awsui_root_ljpwc_1spew_5"><span class="awsui_root_xjuzf_1mnl8_828"><span class="awsui_trigger_xjuzf_1mnl8_864" id="1659-1713832474532-6092"></span></span></span></div></span></span>
Training in benchmark mode using 4 GPU(s)
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for num_gpus=8, torch.cuda.device_count() returns 4 instead of 8. So it's skipped.
Skip because the number of GPUs available[4] is less than 8
🔨Work Item
IMPORTANT:
Project tracker: https://github.com/orgs/dmlc/projects/2
Description
DGL multi-gpu examples fails on single GPU, 4 GPUs, 8GPUs. For num_gpus=0, no stderr is returned. for num_gpus=4, it crashed with below error:
for num_gpus=8,
torch.cuda.device_count()
returns 4 instead of 8. So it's skipped.Report
Depending work items or issues