reorder NEWS

Author: t-kalinowski

NEWS.md

@@ -1,41 +1,68 @@
 # keras3 (development version)
 
-- Added training loop configuration helpers:
-  `config_max_epochs()`, `config_set_max_epochs()`, `config_max_steps_per_epoch()`,
-  and `config_set_max_steps_per_epoch()`. The caps can also be set via the
-  `KERAS_MAX_EPOCHS` and `KERAS_MAX_STEPS_PER_EPOCH` environment variables.
-  Added `config_is_nnx_enabled()` to check whether JAX NNX features are enabled.
+- Expanded numeric operations with `op_layer_normalization()`, `op_cbrt()`,
+  `op_corrcoef()`, `op_deg2rad()`, `op_heaviside()`, the new `op_sparse_sigmoid()`
+  plus matching `activation_sparse_sigmoid()`, and an `attn_logits_soft_cap`
+  argument for `op_dot_product_attention()`.
+
+- Added signal window operations: `op_bartlett()`, `op_blackman()`,
+  `op_hamming()`, `op_hanning()`, and `op_kaiser()`.
+
+- Added `loss_categorical_generalized_cross_entropy()` for training with noisy
+  labels.
 
 - LoRA-enabled layers (`layer_dense()`, `layer_embedding()`, `layer_einsum_dense()`)
   gain a `lora_alpha` argument to scale the adaptation delta independently of the
   chosen rank.
 
-- `Layer$add_weight()` gains an `overwrite_with_gradient` option and
-  layers now provide a `symbolic_call()` method.
+- Added complex-valued helpers: S3 `Arg()` methods for tensors, `op_angle()`,
+  and conversions `op_view_as_real()` / `op_view_as_complex()`.
 
-- `layer_layer_normalization()` removes the `rms_scaling` argument.
+- Added the Muon optimizer via `optimizer_muon()`.
+
+- Added elastic deformation utilities for images: `layer_random_elastic_transform()`
+  and the lower-level `op_image_elastic_transform()`.
 
 - Transposed convolution utilities now follow the latest Keras API:
   `op_conv_transpose()` defaults `strides = 1` and the `layer_conv_*_transpose()`
   layers expose `output_padding` for precise shape control.
 
-- Added the Muon optimizer via `optimizer_muon()`.
-
-- Added `loss_categorical_generalized_cross_entropy()` for training with noisy
-  labels.
-
-- Added elastic deformation utilities for images: `layer_random_elastic_transform()`
-  and the lower-level `op_image_elastic_transform()`.
+- `register_keras_serializable()` now returns a registered Python callable,
+  making it easier to use with bare R functions.
 
 - `save_model_weights()` adds a `max_shard_size` argument to split large weight
   files into manageable shards.
 
+- `keras_variable()` now accepts a `synchronization` argument for distributed
+  strategies.
+
+- `layer_layer_normalization()` removes the `rms_scaling` argument.
+
 - `layer_reshape()` can now accept `-1` as a sentinel for an automatically calculated axis size.
 
 - `layer_torch_module_wrapper()` gains an `output_shape` argument to help Keras
   infer shapes when wrapping PyTorch modules.
 
-- Built-in datasets now accept `convert = FALSE` to return NumPy arrays
+- `Layer$add_weight()` gains an `overwrite_with_gradient` option and
+  layers now provide a `symbolic_call()` method.
+
+- Added `str()` S3 method for Keras Variables.
+
+- Added S3 methods for JAX array:
+  `str()`, `as.array()`, `as.double()`, `as.integer()`, `as.numeric()`.
+
+- Added base-array compatibility methods for backend tensors: `t()`,
+  `aperm()`, and `all.equal()`.
+
+- Added `pillar::type_sum()` for JAX variables and `JaxVariable`;
+  extended `str()` coverage to the new JAX variable class.
+
+- `config_max_epochs()`, `config_set_max_epochs()`, `config_max_steps_per_epoch()`,
+  and `config_set_max_steps_per_epoch()`. The caps can also be set via the
+  `KERAS_MAX_EPOCHS` and `KERAS_MAX_STEPS_PER_EPOCH` environment variables.
+  Added `config_is_nnx_enabled()` to check whether JAX NNX features are enabled.
+
+- Built-in dataset loaders now accept `convert = FALSE` to return NumPy arrays
   instead of R arrays.
 
 - Updated `plot(history, theme_bw = TRUE)` for `ggplot2` 3.4.0
@@ -44,45 +71,18 @@
 - `plot(model)` DPI is now globally configurable via
   `options(keras.plot.model.dpi = )`, (defaults to  `200`).
 
-- Added base-array compatibility methods for backend tensors: `t()`,
-  `aperm()`, and `all.equal()`.
-
 - Reexported reticulate functions: `py_help()`, `py_to_r()`, `r_to_py()`,
   `py_require()`, and `import()`.
 
 - Support `super()$initialize()` in subclassed Keras classes; improved
   `super()` behavior in subclasses.
 
-- Added `pillar::type_sum()` for JAX variables and `JaxVariable`;
-  extended `str()` coverage to the new JAX variable class.
-
-- Added S3 methods for JAX array:
-  `str()`, `as.array()`, `as.double()`, `as.integer()`, `as.numeric()`.
-
-- Added `str()` S3 method for Keras Variables.
-
-- `keras_variable()` now accepts a `synchronization` argument for distributed
-  strategies.
-
 - Updated dependencies declared by `use_backend("jax", gpu=TRUE)`
   for compatability with `keras-hub`.
 
-- Fixed `register_keras_serializable()` when passed bare functions.
-
-- Fixed an issue when switching backends twice in a row.
-
 - Exported `named_list()` utility.
 
-- Added complex-valued helpers: S3 `Arg()` methods for tensors, `op_angle()`,
-  and conversions `op_view_as_real()` / `op_view_as_complex()`.
-
-- Added signal window operations: `op_bartlett()`, `op_blackman()`,
-  `op_hamming()`, `op_hanning()`, and `op_kaiser()`.
-
-- Expanded numeric operations with `op_layer_normalization()`, `op_cbrt()`,
-  `op_corrcoef()`, `op_deg2rad()`, `op_heaviside()`, the new `op_sparse_sigmoid()`
-  plus matching `activation_sparse_sigmoid()`, and an `attn_logits_soft_cap`
-  argument for `op_dot_product_attention()`.
+- Fixed an issue when switching backends twice in a row.
 
 # keras3 1.4.0