Comments (2)
bratao
commented on May 27, 2024
1
Yeah @sharvil , probably this was the problem. I just pip installed, and during the debug that I realized that I was using a older version of cuda. I´m closing to reduce the noise.
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sharvil
commented on May 27, 2024
Thanks for the details, @bratao. Which method did you use to install PyTorch with CUDA 10.0? The official builds on pytorch.org only support 9.2, 10.1, and 10.2 (see prebuilt pip wheels at https://download.pytorch.org/whl/torch_stable.html; conda installs are similar).
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Related Issues (20)
- Install on pip on systems without cuda HOT 7
- Support zoneout on lstm cell state and add recurrent dropout HOT 2
- CUDA error: an illegal memory access was encountered HOT 6
- haste_pytorch: Gradient for kernel/recurrent_kernel becomes zero when trained on gpu HOT 4
- How to expose LayerNormGRUCell to python ? HOT 2
- Can't run haste layers in Keras HOT 12
- Biases in final IndRNN layer are 0 HOT 1
- Zoneout remains during eval() HOT 2
- return_state_sequence for tf version
- layer_norm_gru_cell HOT 1
- Can Bidirectional Rnn and multi-layer Rnn be supported? HOT 1
- Activation function in IndRNN HOT 1
- haste_pytorch does not install properly with conda cudatoolkit? HOT 3
- Feature request for cell classes for pytorch HOT 7
- `RNN`s with `zoneout > 0.0` have wrong gradients HOT 1
- haste_tf compilation fails with "‘bfloat16’ in namespace ‘Eigen’ does not name a type"
- Support for PyTorch packed sequences HOT 2
- Supporting RWKV (a RNN that can match transformer LM & zero-shot performance at 1B+ params)
- Nan loss when replace pytorch LSTM with your LSTM or LayerNormLSTM HOT 2
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