Mention support of cupy, pydata/sparse, ndonnx and others (#337)

* mention support of cupy, change flax and paddle to community level

* pollinate gitignore

* mention compatibility with more frameworks

.gitignore

@@ -112,9 +112,7 @@ design-einops.txt
 # logo and video generation
 logo
 
-# code of internal checks
-_uncommited_explorations
-trash_notebooks
+# any local explorations
 *.personal*
 
 # oneflow's output trash
@@ -126,5 +124,5 @@ docs_src/index.md
 # vs code 
 *.code-workspace
 
-# macos files
+# macos system files
 .DS_Store

README.md

@@ -314,16 +314,19 @@ Einops works with ...
 - [pytorch](https://pytorch.org/)
 - [tensorflow](https://www.tensorflow.org/)
 - [jax](https://github.com/google/jax)
-- [tf.keras](https://www.tensorflow.org/guide/keras)
-- [flax](https://github.com/google/flax) (experimental)
-- [paddle](https://github.com/PaddlePaddle/Paddle) (experimental)
+- [cupy](https://github.com/cupy/cupy)
+- [flax](https://github.com/google/flax) (community)
+- [paddle](https://github.com/PaddlePaddle/Paddle) (community)
 - [oneflow](https://github.com/Oneflow-Inc/oneflow) (community)
 - [tinygrad](https://github.com/tinygrad/tinygrad) (community)
 
 Additionally, starting from einops 0.7.0 einops can be used with any framework that supports [Python array API standard](https://data-apis.org/array-api/latest/API_specification/index.html), which includes
 
 - numpy>=2.0
 - [MLX](https://github.com/ml-explore/mlx), after https://github.com/ml-explore/mlx/pull/1289
+- [pydata/sparse](https://github.com/pydata/sparse) >= 0.15
+- [quantco/ndonnx](https://github.com/Quantco/ndonnx)
+- dask is supported via [array-api-compat](https://github.com/data-apis/array-api-compat)
 
 Previous releases of einops supported `mxnet`, `gluon` and `chainer`.