Add notes about minumum supported versions in the README

Author: asmeurer

README.md

@@ -141,11 +141,29 @@ specification:
   50](https://numpy.org/neps/nep-0050-scalar-promotion.html) and
   https://github.com/numpy/numpy/issues/22341)
 
+- `asarray()` does not support `copy=False`.
+
 - Functions which are not wrapped may not have the same type annotations
   as the spec.
 
 - Functions which are not wrapped may not use positional-only arguments.
 
+The minimum supported NumPy version is 1.21. However, this older version of
+NumPy has a few issues:
+
+- `unique_*` will not compare nans as unequal.
+- `finfo()` has no `smallest_normal`.
+- No `from_dlpack` or `__dlpack__`.
+- `argmax()` and `argmin()` do not have `keepdims`.
+- `qr()` doesn't support matrix stacks.
+- `asarray()` doesn't support `copy=True` (as noted above, `copy=False` is not
+  supported even in the latest NumPy).
+- Type promotion behavior will be value based for 0-D arrays (and there is no
+  `NPY_PROMOTION_STATE=weak` to disable this).
+
+If any of these are an issue, it is recommended to bump your minimum NumPy
+version.
+
 ### PyTorch
 
 - Like NumPy/CuPy, we do not wrap the `torch.Tensor` object. It is missing the
@@ -190,6 +208,8 @@ specification:
 - As with NumPy, type annotations and positional-only arguments may not
   exactly match the spec for functions that are not wrapped at all.
 
+The minimum supported PyTorch version is 1.13.
+
 ## Vendoring
 
 This library supports vendoring as an installation method. To vendor the