:rgba(0,0,0,.05)}.table-hover tbody tr:hover{color:#212529;background-color:rgba(0,0,0,.075)}.table-primary,.table-primary>td,.table-primary>th{background-color:#b8daff}.table-primary tbody+tbody,.table-primary td,.table-primary th,.table-primary thead th{border-color:#7abaff}.table-hover .table-primary:hover{background-color:#9fcdff}.table-hover .table-primary:hover>td,.table-hover .table-primary:hover>th{background-color:#9fcdff}.table-secondary,.table-secondary>td,.table-secondary>th{backgrou...

color: #212529;\n  background-color: rgba(0, 0, 0, 0.075);\n}\n\n.table-primary,\n.table-primary > th,\n.table-primary > td {\n  background-color: #b8daff;\n}\n\n.table-primary th,\n.table-primary td,\n.table-primary thead th,\n.table-primary tbody + tbody {\n  border-color: #7abaff;\n}\n\n.table-hover .table-primary:hover {\n  background-color: #9fcdff;\n}\n\n.table-hover .table-primary:hover > td,\n.table-hover .table-primary:hover > th {\n  background-color: #9fcdff;\n}\n\n.table-secondary,\n.table-secondary...

color: #212529;\n  background-color: rgba(0, 0, 0, 0.075);\n}\n\n.table-primary,\n.table-primary > th,\n.table-primary > td {\n  background-color: #b8daff;\n}\n\n.table-primary th,\n.table-primary td,\n.table-primary thead th,\n.table-primary tbody + tbody {\n  border-color: #7abaff;\n}\n\n.table-hover .table-primary:hover {\n  background-color: #9fcdff;\n}\n\n.table-hover .table-primary:hover > td,\n.table-hover .table-primary:hover > th {\n  background-color: #9fcdff;\n}\n\n.table-secondary,\n.table-secondary...

  network plugins which was first widely noticed in 1.16 (though some users saw it
  earlier than that, possibly only with specific network plugins). If you were previously
  using ethtool to disable checksum offload on your primary network interface, you should
  now be able to stop doing that. ([#92035](https://github.com/kubernetes/kubernetes/pull/92035), [@danwinship](https://github.com/danwinship)) [SIG Network and Node]

*   Keras:

    *   `tf.keras.layers.Conv` now includes a public `convolution_op` method.
        This method can be used to simplify the implementation of Conv
        subclasses. There are two primary ways to use this new method. The first
        is to use the method directly in your own `call` method: `python class
        StandardizedConv2D(tf.keras.layers.Conv2D): def call(self, inputs):