# tf.math.argmax

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|---|---|
| [![](https://www.tensorflow.org/images/tf_logo_32px.png) TensorFlow 1 version](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/math/argmax) | [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.0.0/tensorflow/python/ops/math_ops.py#L141-L184) |

Returns the index with the largest value across axes of a tensor.

#### View aliases


**Main aliases**

[`tf.argmax`](https://www.tensorflow.org/api_docs/python/tf/math/argmax)

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    tf.math.argmax(
        input, axis=None, output_type=tf.dtypes.int64, name=None
    )

Note that in case of ties the identity of the return value is not guaranteed.

#### For example:

    A=tf.constant([2,20,30,3,6]) # Constant 1-D Tensor
    tf.math.argmax(A) # output 2 as index 2 (A[2]) is maximum in tensor A
    B=tf.constant([[2,20,30,3,6],[3,11,16,1,8],[14,45,23,5,27]])
    tf.math.argmax(B,0) # [2, 2, 0, 2, 2]
    tf.math.argmax(B,1) # [2, 2, 1]

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`](https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/dtypes/DType) from: `tf.int32, tf.int64`. Defaults to
[`tf.int64`](https://www.tensorflow.org/versions/r2.0/api_docs/python/tf#int64).
name: A name for the operation (optional).

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| ## Returns ||
|---|---|
| A `Tensor` of type `output_type`. ||

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#### Usage:

    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