tf.math.argmin | TensorFlow v2.16.1 (original) (raw)
tf.math.argmin
Returns the index with the smallest value across axes of a tensor.
View aliases
Main aliases
tf.math.argmin(
input,
axis=None,
output_type=tf.dtypes.int64,
name=None
)
Used in the notebooks
| Used in the guide |
|---|
| Matrix approximation with Core APIs |
Returns the smallest index in case of ties.
| 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 totf.int64. |
| name | A name for the operation (optional). |
| Returns |
|---|
| A Tensor of type output_type. |
Usage:
import tensorflow as tf
a = [1, 10, 26.9, 2.8, 166.32, 62.3]
b = tf.math.argmin(input = a)
c = tf.keras.backend.eval(b)
# c = 0
# here a[0] = 1 which is the smallest element of a across axis 0
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Last updated 2024-04-26 UTC.