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# torch.Tensor.detach

Tensor.detach()

  Returns a new Tensor, detached from the current graph.

  The result will never require gradient.

  This method also affects forward mode AD gradients and the result will never have forward mode AD gradients.

  Note

  Returned Tensor shares the same storage with the original one. In-place modifications on either of them will be seen, and may trigger errors in correctness checks. IMPORTANT NOTE: Previously, in-place size / stride / storage changes (such as resize_ / resize_as_ / set_ / transpose_) to the returned tensor also update the original tensor. Now, these in-place changes will not update the original tensor anymore, and will instead trigger an error. For sparse tensors: In-place indices / values changes (such as zero_ / copy_ / add_) to the returned tensor will not update the original tensor anymore, and will instead trigger an error.

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