- update to 0.6.12:
  * add `torch.indices` and `tensorflow.indices`
- update to 0.6.11:
  * Fix creation functions with builtin `like` kwarg
  * Allow additional keyword arguments in `tensorflow_diag`
- update to 0.6.10:
  * The following functions now inherit default `dtype` and
    possibly `device` (when using torch) when the `like` kwarg is
    an explicit array:
    * `"empty"`
    * `"eye"`
    * `"full"`
    * `"identity"`
    * `"ones"`
    * `"zeros"`
  * fix NumpyMimic special attribute access
  * fix `"diag"` for tensorflow.

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- update to 0.6.9:
  * `autojit`: fix jax when kwargs are used
  * `autojit`: simplify torch and python compiler
  * torch: alias min/max to amin/amax

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- update to 0.6.8:
  * Alias jax.scipy

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- update to 0.6.7:
  * `lazy.einsum`: allow `cotengra` or `opt_einsum` for advanced
    parsing, fall back to basic when neither present
  * add `torch.expand_dims`.
  * **Full Changelog**:
    https://github.com/jcmgray/autoray/compare/v0.6.6...v0.6.7

  * fix: matmul shape for lazy by @yangguohao in #16
- Initial package release.

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- update to 0.6.3:
  * `autoray.lazy.compute`: allow computing multiple outputs
    simultaneously
  * `autoray.lazy.Function` allow pickling and viewing of
    uncompiled source
  * make sure `shape` and `ndim` work for builtins similarly to
    `numpy.{shape,ndim}`
  * Add: `autoray.lazy.where` function for `LazyArray`
  * Add: `autoray.lazy.take` function for `LazyArray`
  * Add`LazyArray.plot_history_stats` pie charts
  * Add `autoray.shape` and `autoray.ndim` as preferred shape
    functions
  * Add basic support for `aesara`
  * `LazyArray`: fix negative axis reductions
  * fix fancy indexing of `LazyArray` objects

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