tf.compat.v1.argmin

Returns the index with the smallest value across axes of a tensor. (deprecated arguments)

View aliases

Compat aliases for migration

tf.compat.v1.math.argmin

tf.compat.v1.argmin(
    input, axis=None, name=None, dimension=None, output_type=tf.dtypes.int64
)

Warning: SOME ARGUMENTS ARE DEPRECATED: (dimension). They will be removed in a future version. Instructions for updating: Use the axis argument instead

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.
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.
name: A name for the operation (optional).

Returns:

A Tensor of type output_type.