Thanks for your response. I have created a new environment and it did worked. But now when I am trying to built a model using pretrained resnet152 to classify images as dog or cat, I am getting the below shared error
RuntimeError: cuDNN error: CUDNN_STATUS_INTERNAL_ERROR
You can try to repro this exception using the following code snippet. If that doesn’t trigger the error, please include your original repro script when reporting this issue.
import torch
torch.backends.cuda.matmul.allow_tf32 = True
torch.backends.cudnn.benchmark = True
torch.backends.cudnn.deterministic = False
torch.backends.cudnn.allow_tf32 = True
data = torch.randn([8, 3, 224, 224], dtype=torch.float, device=‘cuda’, requires_grad=True)
net = torch.nn.Conv2d(3, 64, kernel_size=[7, 7], padding=[3, 3], stride=[2, 2], dilation=[1, 1], groups=1)
net = net.cuda().float()
out = net(data)
out.backward(torch.randn_like(out))
torch.cuda.synchronize()
ConvolutionParams
data_type = CUDNN_DATA_FLOAT
padding = [3, 3, 0]
stride = [2, 2, 0]
dilation = [1, 1, 0]
groups = 1
deterministic = false
allow_tf32 = true
input: TensorDescriptor 000001EEFAEB3EB0
type = CUDNN_DATA_FLOAT
nbDims = 4
dimA = 8, 3, 224, 224,
strideA = 150528, 50176, 224, 1,
output: TensorDescriptor 000001EEFAEB3F20
type = CUDNN_DATA_FLOAT
nbDims = 4
dimA = 8, 64, 112, 112,
strideA = 802816, 12544, 112, 1,
weight: FilterDescriptor 000001EEF64CF9E0
type = CUDNN_DATA_FLOAT
tensor_format = CUDNN_TENSOR_NCHW
nbDims = 4
dimA = 64, 3, 7, 7,
Pointer addresses:
input: 0000000505400000
output: 0000000560400000
weight: 000000054F3E9000
Can you tell me where am I going wrong?