keras3 1.1.0

• Fixed issue where GPUs would not be found when running on Windows under WSL Linux.
  (reported in #1456, fixed in #1459)

• keras_shape objects (as returned by keras3::shape()) gain == and != methods.

• Fixed warning from tfruns::training_run() being unable to log optimizer learning rate.

• Added compatibility with Keras v3.4.1 (no R user facing changes).

• Added compatibility with Keras v3.4.0. User facing changes:

  • New functions:

    • op_argpartition()
    • op_map()
    • op_scan()
    • op_switch()
    • op_dtype()
    • op_lstsq()
    • op_image_hsv_to_rgb()
    • op_image_rgb_to_hsv()

  • Changes:

    • Added support for arbitrary, deeply nested input/output structures in
      Functional models (e.g. lists of lists of lists of inputs or outputs...)
    • Add support for optional Functional inputs.
      • keras_input() gains an optional argument.
      • keras_model_sequential() gains a input_optional argument.
    • Add support for float8 inference for Dense and EinsumDense layers.
    • Enable layer_feature_space() to be used in a {tfdatasets} pipeline even
      when the backend isn't TensorFlow.
    • layer_string_lookup() can now take tf$SparseTensor() as input.
    • layer_string_lookup() returns "int64" dtype by default in more modes now.
    • Layer() instances gain attributes path and quantization_mode.
    • Metric()$variables is now recursive.
    • Add training argument to Model$compute_loss().
    • split_dataset() now supports nested structures in dataset.
    • All applications gain a name argument, accept a custom name.
    • layer_multi_head_attention() gains a seed argument.
    • All losses gain a dtype argument.
    • loss_dice() gains an axis argument.
    • op_ctc_decode(), new default for mask_index = 0
    • All op_image_* functions now use default data_format value
      to config_image_data_format()
    • op_isclose() gains arguments rtol, atol, equal_nan.
    • save_model() gains argument zipped.
    • Bugs fixes and performance improvements.