Doc issue on the description of `edge_order` in `torch.gradient()`

[ILCSFNO]

📚 The doc issue

The doc of torch.gradient() shows its description as below:

pytorch/torch/_torch_docs.py

Lines 4741 to 4744 in 16c0ccd

	edge_order (``int``, optional): 1 or 2, for `first-order
	<https://www.ams.org/journals/mcom/1988-51-184/S0025-5718-1988-0935077-0/S0025-5718-1988-0935077-0.pdf>`_ or
	`second-order <https://www.ams.org/journals/mcom/1988-51-184/S0025-5718-1988-0935077-0/S0025-5718-1988-0935077-0.pdf>`_
	estimation of the boundary ("edge") values, respectively.

For some limitations that usually happen below, which should be noted in docs:

pytorch/aten/src/ATen/native/ReduceOps.cpp

Lines 1043 to 1054 in f5e2de9

	if (dim.has_value()) {
	// The following function get called to check whether dim argument satisfies prerequisites.
	// The output of the function is not used for the computation of gradient.
	dim_list_to_bitset(dim.value(), self.dim());
	for (const auto i : c10::irange(dim.value().size())) {
	TORCH_CHECK(self.size(dim.value()[i]) >= edge_order + 1, "torch.gradient expected each dimension size to be at least edge_order+1");
	}
	} else {
	for (const auto i : c10::irange(self.dim())) {
	TORCH_CHECK(self.size(i) >= edge_order + 1, "torch.gradient expected each dimension size to be at least edge_order+1");
	}
	}

Here is a repro:

Repro

import torch
input_data = torch.randn(10, 2, 32, 32)
gradient = torch.gradient(input_data, spacing=1, dim=None, edge_order=2)

Output

RuntimeError: torch.gradient expected each dimension size to be at least edge_order+1

Thanks for noting!

Suggest a potential alternative/fix

• Fix the Doc of the description of edge_order

[ILCSFNO]

PR opened here:

• Fix the Doc issue on the description of edge_order in torch.gradient() #159130