Failed to determine best cudnn convolution algorithm/No GPU/TPU found

RTX3080 / cuda11.1/cudnn 8.2.1/ubuntu16.04

This problem occurs in jaxlib-0.1.72+cuda111. When I update to 0.1.74, it will disappear. However, in 0.1.74, Jax cannot detect the existence of GPU, and tensorflow can

Therefore, whether I use 0.1.72 or 0.1.74, there is always a problem with me

`RuntimeError: UNKNOWN: Failed to determine best cudnn convolution algorithm: INTERNAL: All algorithms tried for %custom-call.1 = (f32[1,112,112,64]{2,1,3,0}, u8[0]{0}) custom-call(f32[1,229,229,3]{2,1,3,0} %pad, f32[7,7,3,64]{1,0,2,3} %copy.4), window={size=7x7 stride=2x2}, dim_labels=b01f_01io->b01f, custom_call_target=“__cudnn$convForward”, metadata={op_type=“conv_general_dilated” op_name=“jit(conv_general_dilated)/conv_general_dilated[\n batch_group_count=1\n dimension_numbers=ConvDimensionNumbers(lhs_spec=(0, 3, 1, 2), rhs_spec=(3, 2, 0, 1), out_spec=(0, 3, 1, 2))\n feature_group_count=1\n lhs_dilation=(1, 1)\n lhs_shape=(1, 224, 224, 3)\n padding=((2, 3), (2, 3))\n precision=None\n preferred_element_type=None\n rhs_dilation=(1, 1)\n rhs_shape=(7, 7, 3, 64)\n window_strides=(2, 2)\n]” source_file=“/media/node/Materials/anaconda3/envs/xmcgan/lib/python3.9/site-packages/flax/linen/linear.py” source_line=282}, backend_config=“{"algorithm":"0","tensor_ops_enabled":false,"conv_result_scale":1,"activation_mode":"0","side_input_scale":0}” failed. Falling back to default algorithm.

Convolution performance may be suboptimal. To ignore this failure and try to use a fallback algorithm, use XLA_FLAGS=–xla_gpu_strict_conv_algorithm_picker=false. Please also file a bug for the root cause of failing autotuning. `