Returns the index with the smallest value across dimensions of a tensor.
tf.compat.v1.arg_min(
input, dimension, output_type=tf.dtypes.int64, name=None
)
Note that in case of ties the identity of the return value is not guaranteed.
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
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.
|
dimension
|
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 dimension of the input Tensor to reduce across. For vectors,
use dimension = 0.
|
output_type
|
An optional tf.DType from: tf.int32, tf.int64. Defaults to tf.int64.
|
name
|
A name for the operation (optional). |
Returns | |
|---|---|
A Tensor of type output_type.
|