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, int64, bfloat16, uint16, half, uint32, uint64, qint8, quint8, qint32, qint16, quint16, bool.
axis
A Tensor. Must be one of the following types: int16, int32, int64.
int16, 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.int16, tf.uint16, tf.int32, tf.int64. Defaults to tf.int64.
[[["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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.compat.v1.argmax\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/math_ops.py#L245-L259) |\n\nReturns the index with the largest value across axes of a tensor. (deprecated arguments)\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.math.argmax`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/argmax)\n\n\u003cbr /\u003e\n\n tf.compat.v1.argmax(\n input,\n axis=None,\n name=None,\n dimension=None,\n output_type=../../../tf/dtypes#int64\n )\n\n### Used in the notebooks\n\n| Used in the tutorials |\n|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| - [Fitting Dirichlet Process Mixture Model Using Preconditioned Stochastic Gradient Langevin Dynamics](https://www.tensorflow.org/probability/examples/Fitting_DPMM_Using_pSGLD) - [Classify Flowers with Transfer Learning](https://www.tensorflow.org/hub/tutorials/image_feature_vector) - [Exploring the TF-Hub CORD-19 Swivel Embeddings](https://www.tensorflow.org/hub/tutorials/cord_19_embeddings) |\n\n| **Deprecated:** 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\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Usage ----- ||\n|---|---|\n| \u003cbr /\u003e import tensorflow as tf a = [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 \u003cbr /\u003e ||\n\n\u003cbr /\u003e\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`, `int64`, `bfloat16`, `uint16`, `half`, `uint32`, `uint64`, `qint8`, `quint8`, `qint32`, `qint16`, `quint16`, `bool`. |\n| `axis` | A `Tensor`. Must be one of the following types: `int16`, `int32`, `int64`. int16, 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.int16, tf.uint16, 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"]]