CUDNN_STATUS_BAD_PARAM cuda runtime_error ai_generated true

运行时错误：cuDNN 错误：调用 cudnnRNNForwardTraining 时输入大小不匹配导致 CUDNN_STATUS_BAD_PARAM

RuntimeError: cuDNN error: CUDNN_STATUS_BAD_PARAM when calling cudnnRNNForwardTraining with input size mismatch

ID: cuda/cudnn-rnn-bad-dims

其他格式: JSON · Markdown 中文 · English
80%修复率
84%置信度
1证据数
2023-11-05首次发现

版本兼容性

版本状态引入弃用备注
cuDNN 8.9.2 active — — —
CUDA 12.0 active — — —
PyTorch 2.1.0 active — — —
TensorFlow 2.14 active — — —

根因分析

RNN 层的输入张量的特征维度与 cuDNN RNN 描述符中定义的预期输入大小不匹配，或者各层之间的批次大小不一致。

English

The input tensor to an RNN layer has a feature dimension that does not match the expected input size defined in the cuDNN RNN descriptor, or the batch size is inconsistent between layers.

generic

官方文档

https://docs.nvidia.com/deeplearning/cudnn/api/index.html#cudnnRNNForwardTraining

解决方案

  1. import torch; rnn = torch.nn.LSTM(input_size=128, hidden_size=256, num_layers=2); input_tensor = torch.randn(10, 32, 128); output, _ = rnn(input_tensor)
  2. rnn = torch.nn.LSTM(input_size=128, hidden_size=256, batch_first=True); input_tensor = torch.randn(32, 10, 128)

无效尝试

常见但无效的做法:

  1. 90% 失败

    Layer count does not affect the input dimension mismatch; the error is about the first layer's input size.

  2. 85% 失败

    The input dimension requirement is independent of cell type; the mismatch persists.