How to input a numpy array to a neural network in pytorch?

Question

This is the neural network that I defined

class generator(nn.Module):
def __init__(self, n_dim, io_dim):
    super().__init__()
    self.gen = nn.Sequential(
        nn.Linear(n_dim,64),
        nn.LeakyReLU(.01),
        nn.Linear(64, io_dim),
    )

def forward(self, x):
    return self.gen(x)
#The input x is:
x = numpy.random.dirichlet([10,6,3],3)

Now I want the neural network to take dirichlet distributed samples (sampled using numpy.random.dirichlet([10,6,3],10) ) as an input. How to do that?

Asked By: Anik Chaudhuri

||

Source

Answer 1

You need to convert numpy.array to torch.Tensor:

input_tensor = torch.from_numpy(x)

Answered By: Craig.Li

Answer 2

To input a NumPy array to a neural network in PyTorch, you need to convert numpy.array to torch.Tensor. To do that you need to type the following code.

input_tensor = torch.from_numpy(x)

After this, your numpy.array is converted to torch.Tensor.

Answered By: Aanshumaan Shrijai

Answer 3

Instead of using numpy to sample from a dirichlet distribution, use pytorch. Here is the code:

y = torch.Tensor([[10,6,3]])
m = torch.distributions.dirichlet.Dirichlet(y)
z=m.sample()

gen = generator(3,3)
gen(z)

Answered By: Anik Chaudhuri

How to input a numpy array to a neural network in pytorch?

Question:

Answers: