Returns the type from applying the Keras type promotion rules.
tf.keras.backend.result_type(*dtypes)
In general, each argument is first parsed by backend.standardize_dtype,
and the resulting dtype is determined by the least upper bound of the type
promotion lattice.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-06-07 UTC."],[],[],null,["# tf.keras.backend.result_type\n\n\u003cbr /\u003e\n\n|-----------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/keras-team/keras/tree/v3.3.3/keras/src/backend/common/dtypes.py#L272-L311) |\n\nReturns the type from applying the Keras type promotion rules. \n\n tf.keras.backend.result_type(\n *dtypes\n )\n\nIn general, each argument is first parsed by [`backend.standardize_dtype`](../../../tf/keras/backend/standardize_dtype),\nand the resulting dtype is determined by the least upper bound of the type\npromotion lattice.\n| **Note:** This function attempts to match the result of `jnp.result_type`.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------|---------------|\n| `dtypes` | Input dtypes. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| The result dtype. ||\n\n\u003cbr /\u003e\n\n#### Examples:\n\n x = keras.ops.ones((1,), dtype=\"bfloat16\")\n keras.backend.result_type(x.dtype, int)\n \"bfloat16\"\n\n x = keras.ops.ones((1,), dtype=\"int32\")\n y = keras.ops.ones((1,), dtype=\"float32\")\n keras.backend.result_type(x.dtype, y.dtype)\n \"float32\""]]