Add instance methods tensor.isnan(), tensor.isinf(), tensor.isfinite()

[ShawnZhong]

Fix #37736

[dr-ci]

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This comment has been revised 9 times.

[choidongyeon]

Hey @ShawnZhong, could you help me understand how this PR fixes the issue? Just curious 😄

[ShawnZhong]

@choidongyeon

pytorch/aten/src/ATen/native/README.md

Lines 197 to 220 in 681c6fb

	### `variants`
	```
	variants: function, method
	```
	Controls whether Tensor method (`t.foo()`) or namespace Function (`at::foo()`) is
	generated as a result of this declaration. If the declaration is a method,
	you must have an argument `Tensor self` at some position in the method;
	in the method variant this argument will be elided from the argument
	list. For example, given the declaration `where(BoolTensor cond, Tensor self, Tensor other)`,
	this generates the function `at::where(cond, self, other)` and the method
	`self.where(cond, other)`.
	By default, ATen generates only the function variant for a native function.
	When should you also generate a method variant? Tensor operations as methods
	are appropriate for "core" Tensor operations (e.g., add, sub, etc.), but not for
	more complicated neural network layers (e.g., `conv2d`) and internal functions
	designed specifically for binding (e.g., `cudnn_convolution`).
	As we progress along our schema unification of the `func` schema with the JIT
	signature schema, we must introduce features that allow us to increase compliance.
	One of these features are Tensor annotations. As of now we use naming conventions
	to indicate whether an argument of a function is going to be mutated and returned.

[ShawnZhong]

Since this PR has been around for a while, is there anyone who'd like to review this PR?

@gchanan @soumith

[soumith]

lgtm

[facebook-github-bot]

@soumith is landing this pull request. If you are a Facebook employee, you can view this diff on Phabricator.

[facebook-github-bot]

@soumith merged this pull request in 5f9b903.