* If you use masked losses with Keras the loss values may be different in TensorFlow `2.12` compared to previous versions.
 * In cases where the mask was previously ignored, you will now get an error if you pass a mask with an incompatible shape.

### Major Features and Improvements

`tf.keras`:

                    additionalProperties:
                      description: |-
                        AnnotationValue is the value of an annotation in Gateway API. This is used
                        for validation of maps such as TLS options. This roughly matches Kubernetes
                        annotation validation, although the length validation in that case is based
                        on the entire size of the annotations struct.

              }
            ],
            "description": "nodePublishSecretRef is a reference to the secret object containing sensitive information to pass to the CSI driver to complete the CSI NodePublishVolume and NodeUnpublishVolume calls. This field is optional, and  may be empty if no secret is required. If the secret object contains more than one secret, all secret references are passed."

        "type": "object"
      },

This op simulates the precision loss from the quantized forward pass by:

1. Quantizing the tensor to fixed point numbers, which should match the target
   quantization method when it is used in inference.
2. Dequantizing it back to floating point numbers for the following ops, most
   likely matmul.

There are different ways to quantize. This version uses only scaling, so 0.0
maps to 0.

		{"LOG_USER", Const, 1},
		{"LOG_UUCP", Const, 1},
		{"LOG_WARNING", Const, 0},
		{"New", Func, 0},
		{"NewLogger", Func, 0},
		{"Priority", Type, 0},
		{"Writer", Type, 0},
	},
	"maps": {
		{"Clone", Func, 21},
		{"Copy", Func, 21},
		{"DeleteFunc", Func, 21},
		{"Equal", Func, 21},
		{"EqualFunc", Func, 21},
	},
	"math": {
		{"Abs", Func, 0},
		{"Acos", Func, 0},