Summary of the use of argmax function of tensorflow in Python

In TensorFlow,argmax()Functions are a very important operation that returns the index of the maximum value of a given tensor along a specified axis. This function is very common in machine learning and deep learning applications, especially in classification problems, when we need to determine which category has the highest prediction probability.

Basic usage of argmax() function

argmax()The general form of the function is as follows:

(
    input,
    axis=None,
    name=None,
    dimension=None,  # Deprecated, please use axis    output_type=tf.int64
)

input: A tensor that represents the tensor from which to find the maximum value.
axis: An integer specifying the axis along which the maximum value is to be found. If not specified, the entire tensor flattenes by default and returns the index of a single maximum.
name: The name of the operation (optional).
dimension: Deprecated parameters, used before to specify the axis, should now be usedaxis。
output_type: Returns the index data type, default istf.int64。

Example

Suppose we have a two-dimensional tensor that represents the predicted probability of different categories on different samples:

import tensorflow as tf

# Create a two-dimensional tensor with shape [3, 2]predictions = ([[0.1, 0.9], [0.8, 0.2], [0.3, 0.7]], dtype=tf.float32)

# Find the index of the maximum value along the last axis (axis=1)class_indices = (predictions, axis=1)

# Create a TensorFlow session and run it (this is required in TensorFlow, which is not usually required in TensorFlow)# with () as sess:
#     print((class_indices))

# In TensorFlow, you can run it directlyprint(class_indices.numpy())  # use .numpy() Method will TensorFlow Tensor conversion to NumPy Array（exist Eager Execution In mode）

The output will be:

[1 0 1]

This means that the most likely category for the first sample is the category with index 1, the second sample is the category with index 0, and the third sample is the category with index 1. Things to note

In TensorFlow, Eager Execution is enabled by default, so you can run tensor operations directly without creating sessions.
argmax()The function returns the index of the maximum value, not the maximum value itself.
If your tensor contains multiple maximum values (although this is unlikely in most cases unless there is a specific symmetry or repeated values),argmax()The function will return the index of the first maximum value found.
When dealing with classification problems, you will usuallyargmax()The function is applied to the output of the model (i.e. predicted probability) to determine the most likely category for each sample.

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