tf.raw_ops.ArgMin

Returns the index with the smallest value across dimensions of a tensor.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.raw_ops.ArgMin

tf.raw_ops.ArgMin(
    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, bool.
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.