Описание
PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True.
A consistency flaw has been discovered in the PyTorch library. PyTorch has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True.
Меры по смягчению последствий
Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability.
Затронутые пакеты
| Платформа | Пакет | Состояние | Рекомендация | Релиз |
|---|---|---|---|---|
| OpenShift Lightspeed | openshift-lightspeed/lightspeed-service-api-rhel9 | Fix deferred | ||
| OpenShift Lightspeed | openshift-lightspeed-tech-preview/lightspeed-rag-tool-rhel9 | Fix deferred | ||
| Red Hat AI Inference Server | rhaiis-preview/vllm-cuda-rhel9 | Fix deferred | ||
| Red Hat AI Inference Server | rhaiis/vllm-cuda-rhel9 | Fix deferred | ||
| Red Hat AI Inference Server | rhaiis/vllm-rocm-rhel9 | Fix deferred | ||
| Red Hat AI Inference Server | rhaiis/vllm-tpu-rhel9 | Fix deferred | ||
| Red Hat Ansible Automation Platform 2 | ansible-automation-platform-24/de-minimal-rhel8 | Fix deferred | ||
| Red Hat Ansible Automation Platform 2 | ansible-automation-platform-24/de-minimal-rhel9 | Fix deferred | ||
| Red Hat Ansible Automation Platform 2 | ansible-automation-platform-24/de-supported-rhel8 | Fix deferred | ||
| Red Hat Ansible Automation Platform 2 | ansible-automation-platform-24/de-supported-rhel9 | Fix deferred |
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Дополнительная информация
Статус:
EPSS
4 Medium
CVSS3
Связанные уязвимости
PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True.
PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True.
PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True.
PyTorch before 3.7.0 has a bernoulli_p decompose function in decomposi ...
PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True.
EPSS
4 Medium
CVSS3