英文:
RuntimeError: Expected all tensors to be on the same device, but found at least two devices
问题
RuntimeError: 预期所有张量位于相同设备上，但发现至少有两个设备，cuda:0 和 cpu！(在检查方法wrapper_mm中参数mat2的参数时)
我尝试在GPU上运行此代码并打印标签，但出现了此错误。我的训练代码如下：
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') # 设备为cudawith open('intents.json') as f:intents = json.load(f)file = 'data.pth'data = torch.load(file)input_size = data['input_size']model_state = data['model_state']output_size = data['output_size']hidden_size = data['hidden_size']all_words = data['all_words']tags = data['tags']model = NeuralNetwork(input_size, hidden_size, output_size)model.load_state_dict(model_state)model.eval()@jit(target_backend='cuda')def get_response(pattern):sentence = tokenize(pattern)BoW = bag_of_word(sentence, all_words)BoW = torch.from_numpy(BoW).to(device)output = model.forward_propagation(BoW)# print(output)_, predicted = torch.max(output, dim=-1)tag = tags[predicted.item()] # 给出输入语音的预测标签# print(tag)probs = torch.softmax(output, dim=-1) # 使输出概率在-1和1之间# print(props)prob = probs[predicted.item()] # 选择最大概率# print(prob)return prob, tagpattern = speech_to_text()prob, tag = get_response(pattern)print(tag)
英文:
I have gotten the response from the chatbot using GPU, i get the following errors:
RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! (when checking argument for argument mat2 in method wrapper_mm)
I tried running this code on GPU and print tag but I get on this error.
My training code is as follows:
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') # device = cudawith open('intents.json') as f:intents = json.load(f)file = 'data.pth'data = torch.load(file)input_size = data['input_size']model_state = data['model_state']output_size = data['output_size']hidden_size = data['hidden_size']all_words = data['all_words']tags = data['tags']model = NeuralNetwork(input_size,hidden_size,output_size)model.load_state_dict(model_state)model.eval()@jit(target_backend='cuda')def get_response(pattern):sentence = tokenize(pattern)BoW = bag_of_word(sentence,all_words)BoW = torch.from_numpy(BoW).to(device)output = model.forward_propagation(BoW)# print(output)_,predicted = torch.max(output,dim=-1)tag = tags[predicted.item()] # give prediction tag for input speech# print(tag)probs = torch.softmax(output,dim=-1) # to make output probability between -1 and 1# print(props)prob = probs[predicted.item()] # to select the big probability# print(prob)return prob,tagpattern = speech_to_text()prob,tag = get_response(pattern)print(tag)
答案1
得分: 1
将模型 to() 移动到设备上：
model = NeuralNetwork(input_size, hidden_size, output_size).to(device)
英文:
Move the model to() the device:
model = NeuralNetwork(input_size, hidden_size, output_size).to(device)
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