Improvements in TensorFlow Type Promotion Reduce Bit-Widening Risks | HackerNoon
Briefly

Turning on the new type promotion results in more consistent and predictable promotion outcomes. It reduces the risk of bit-widening during operations. Tensor operations now allow implicit conversions, with tf.Tensor methods and tf.Variable in-place operations utilizing this feature. tf.constant can return WeakTensor, even allowing for implicit conversions with differing dtypes. Additionally, using a lattice-based system helps ensure reliable promotion results, contrasting with the previous method that produced inconsistent outcomes based on operation order.
The new type promotion produces more consistent and predictable promotion results, reducing the risk of bit-widening and allowing for implicit conversions in tensor operations.
TensorFlow's tf.Tensor mathematical dunder methods use the new type promotion, enabling implicit conversions when tensor inputs have different dtypes.
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