eye¶

dragon.vm.torch.eye(
  n,
  m=None,
  out=None,
  dtype='float32',
  device=None,
  requires_grad=False
)[source]¶

Return a tensor constructed as the identity matrix.

\[\text{out} \leftarrow \text{diag}(1, 1, ..., 1) \]

The rows and cols of matrix are determined by n and m:

print(torch.eye(2))  # [[1., 0.], [0., 1.]]
print(torch.eye(2, 3))  # [[1., 0., 0.], [0., 1., 0.]]

Parameters:

• n (int) – The number output rows.
• m (int, optional) – The number output cols.
• out (dragon.vm.torch.Tensor, optional) – The output tensor.
• dtype (str, optional, default='float32') – The data type of output tensor.
• device (dragon.vm.torch.device, optional) – The device of output tensor.
• requires_grad (bool, optional, default=False) – Record gradient for output tensor or not.

Returns:

dragon.vm.torch.Tensor – The output tensor.