Returns the index with the smallest value across axes of a tensor.
tf.compat.v2.argmin( 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.
Args | |
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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 | |
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A Tensor of type output_type . |
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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Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/compat/v2/argmin