05/25/2023 17:40:41 - INFO - __main__ - ***** Running training ***** 05/25/2023 17:40:41 - INFO - __main__ - Num examples = 833 05/25/2023 17:40:41 - INFO - __main__ - Num Epochs = 72 05/25/2023 17:40:41 - INFO - __main__ - Instantaneous batch size per device = 1 05/25/2023 17:40:41 - INFO - __main__ - Total train batch size (w. parallel, distributed & accumulation) = 4 05/25/2023 17:40:41 - INFO - __main__ - Gradient Accumulation steps = 4 05/25/2023 17:40:41 - INFO - __main__ - Total optimization steps = 15000 Steps: 0%| | 0/15000 [00:00 main() File "lora_test_1.py", line 728, in main latents = vae.encode(batch["pixel_values"].to(dtype=weight_dtype)).latent_dist.sample() File "/home/long.qul/miniconda3/envs/triton/lib/python3.8/site-packages/diffusers/utils/accelerate_utils.py", line 46, in wrapper return method(self, *args, **kwargs) File "/home/long.qul/miniconda3/envs/triton/lib/python3.8/site-packages/diffusers/models/autoencoder_kl.py", line 164, in encode h = self.encoder(x) File "/home/long.qul/miniconda3/envs/triton/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "/home/long.qul/miniconda3/envs/triton/lib/python3.8/site-packages/diffusers/models/vae.py", line 109, in forward sample = self.conv_in(sample) File "/home/long.qul/miniconda3/envs/triton/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "/home/long.qul/miniconda3/envs/triton/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 463, in forward return self._conv_forward(input, self.weight, self.bias) File "/home/long.qul/miniconda3/envs/triton/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 459, in _conv_forward return F.conv2d(input, weight, bias, self.stride, RuntimeError: cuDNN error: CUDNN_STATUS_NOT_INITIALIZED