torch.from_numpy().to(torch.float32)
时间: 2023-06-08 07:07:49 浏览: 173
这个语句的作用是将一个numpy的数组转换成PyTorch张量,并将dtype设置为float32。具体来说,torch.from_numpy()将numpy数组转换为PyTorch张量,而to(torch.float32)将张量的数据类型转换为float32。这通常是在将numpy数组作为PyTorch模型的输入时使用。
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torch.from_numpy(state).float()
该行代码是将一个numpy数组state转换为PyTorch中的Tensor,并将其数据类型转换为float类型。torch.from_numpy()函数是PyTorch中的一个函数,它可以将numpy数组转化为PyTorch中的Tensor,共享内存,两者数据共享,即如果修改numpy数组,Tensor也会改变,反之亦然。这样可以在不拷贝数据的情况下,方便地将numpy数组与PyTorch中的Tensor进行转换。在这里,state是一个numpy数组,通过torch.from_numpy(state)将其转换为PyTorch中的Tensor,然后通过.float()方法将其数据类型转换为float类型,以便后续使用。
torch.from_numpy(signal).float()
This function converts a NumPy array to a PyTorch tensor with a floating-point data type.
Specifically, it takes in a NumPy array called "signal" and returns a PyTorch tensor with the same data as "signal", but with a floating-point data type (i.e. each value will be a decimal instead of an integer).
This function can be useful if you have data stored in a NumPy array and want to use it in a PyTorch model, since PyTorch tensors are the preferred data type for working with neural networks.