My model:
# Fully connected neural network with one hidden layer
class GRU_Model(nn.Module):
def __init__(self, input_size, hidden_size, num_layers, num_classes):
super(GRU_Model, self).__init__()
self.num_layers = num_layers
self.hidden_size = hidden_size
self.gru = nn.GRU(input_size, hidden_size, num_layers, batch_first=True)
# -> x needs to be: (batch_size, seq, input_size)
# or:
#self.gru = nn.GRU(input_size, hidden_size, num_layers, batch_first=True)
#self.lstm = nn.LSTM(input_size, hidden_size, num_layers, batch_first=True)
self.fc = nn.Linear(hidden_size, num_classes)
def forward(self, x):
# Set initial hidden states (and cell states for LSTM)
h0 = torch.zeros(self.num_layers, x.size(0), self.hidden_size).to(device)
# Forward propagate RNN
out, _ = self.gru(x, h0)
# Decode the hidden state of the last time step
out = out[:, -1, :]
# out: (n, 128)
out = self.fc(out)
# out: (n, 10)
return out
Still found the same problem, but the previous time this model worked and I update the dataset, now It gives the same error, I update the driver and all dependencies also. I wave all information below. Please someone assist me. Thanks in advance.
Collecting environment information...
PyTorch version: 1.13.1
Is debug build: False
CUDA used to build PyTorch: 11.7
ROCM used to build PyTorch: N/A
OS: Microsoft Windows 10 Pro
GCC version: (Rev5, Built by MSYS2 project) 5.3.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: N/A
Python version: 3.7.13 (default, Mar 28 2022, 08:03:21) [MSC v.1916 64 bit (AMD64)] (64-bit runtime)
Python platform: Windows-10-10.0.19041-SP0
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:
GPU 0: GeForce RTX 2080 SUPER
GPU 1: GeForce RTX 2080 SUPER
Nvidia driver version: 461.40
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
Versions of relevant libraries:
[pip3] mypy==0.910
[pip3] mypy-extensions==0.4.3
[pip3] numpy==1.21.5
[pip3] pytorch-lightning==1.7.0
[pip3] pytorch-model-summary==0.1.1
[pip3] pytorch-tools==0.4.0
[pip3] pytorchtools==0.0.2
[pip3] torch==1.13.1
[pip3] torchaudio==0.13.1
[pip3] torchmetrics==0.9.3
[pip3] torchsummary==1.5.1
[pip3] torchvision==0.14.1
[pip3] torchviz==0.0.2
[conda] blas 1.0 mkl
[conda] cudatoolkit 10.0.130 0
[conda] mkl 2021.4.0 haa95532_640
[conda] mkl-service 2.4.0 py37h2bbff1b_0
[conda] mkl_fft 1.3.1 py37h277e83a_0
[conda] mkl_random 1.2.2 py37hf11a4ad_0
[conda] numpy 1.20.3 pypi_0 pypi
[conda] numpy-base 1.21.5 py37hca35cd5_3
[conda] pytorch 1.13.1 py3.7_cuda11.7_cudnn8_0 pytorch
[conda] pytorch-cuda 11.7 h16d0643_5 pytorch
[conda] pytorch-lightning 1.7.0 pypi_0 pypi
[conda] pytorch-model-summary 0.1.1 py_0 conda-forge
[conda] pytorch-mutex 1.0 cuda pytorch
[conda] pytorch-tools 0.4.0 pypi_0 pypi
[conda] pytorchtools 0.0.2 pypi_0 pypi
[conda] torchaudio 0.13.1 pypi_0 pypi
[conda] torchmetrics 0.9.3 pypi_0 pypi
[conda] torchsummary 1.5.1 pypi_0 pypi
[conda] torchvision 0.13.0 pypi_0 pypi
[conda] torchviz 0.0.2 pypi_0 pypi