Note that in case of ties the identity of the return value is not guaranteed.
Usage:
importtensorflowastfa=[1,10,26.9,2.8,166.32,62.3]b=tf.math.argmax(input=a)c=tf.keras.backend.eval(b)# c = 4# here a[4] = 166.32 which is the largest element of a across axis 0
Args
input
A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, complex64, int64, qint8, quint8, qint32, bfloat16, uint16, complex128, half, uint32, uint64.
axis
A Tensor. Must be one of the following types: int32, int64.
int32 or int64, must be in the range [-rank(input), rank(input)).
Describes which axis of the input Tensor to reduce across. For vectors,
use axis = 0.
output_type
An optional tf.DType from: tf.int32, tf.int64. Defaults to tf.int64.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.math.argmax\n\n\u003cbr /\u003e\n\n|---------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 2 version](/api_docs/python/tf/math/argmax) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/ops/math_ops.py#L125-L138) |\n\nReturns the index with the largest value across axes of a tensor. (deprecated arguments)\n\n#### View aliases\n\n\n**Main aliases**\n\n[`tf.argmax`](/api_docs/python/tf/math/argmax)\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.argmax`](/api_docs/python/tf/compat/v1/argmax), [`tf.compat.v1.math.argmax`](/api_docs/python/tf/compat/v1/argmax)\n\n\u003cbr /\u003e\n\n tf.math.argmax(\n input, axis=None, name=None, dimension=None, output_type=tf.dtypes.int64\n )\n\n| **Warning:** SOME ARGUMENTS ARE DEPRECATED: `(dimension)`. They will be removed in a future version. Instructions for updating: Use the `axis` argument instead\n\nNote that in case of ties the identity of the return value is not guaranteed.\n\n#### Usage:\n\n import tensorflow as tf\n a = [1, 10, 26.9, 2.8, 166.32, 62.3]\n b = tf.math.argmax(input = a)\n c = tf.keras.backend.eval(b)\n # c = 4\n # here a[4] = 166.32 which is the largest element of a across axis 0\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `input` | A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `uint8`, `int16`, `int8`, `complex64`, `int64`, `qint8`, `quint8`, `qint32`, `bfloat16`, `uint16`, `complex128`, `half`, `uint32`, `uint64`. |\n| `axis` | A `Tensor`. Must be one of the following types: `int32`, `int64`. int32 or int64, must be in the range `[-rank(input), rank(input))`. Describes which axis of the input Tensor to reduce across. For vectors, use axis = 0. |\n| `output_type` | An optional [`tf.DType`](../../tf/dtypes/DType) from: `tf.int32, tf.int64`. Defaults to [`tf.int64`](../../tf#int64). |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor` of type `output_type`. ||\n\n\u003cbr /\u003e"]]