How to decode a tensorflow summary string?

@shyann 

To decode a TensorFlow summary string, you can use the tf.io.parse_single_example function from the TensorFlow library. Here is an example code snippet that demonstrates how to decode a TensorFlow summary string:

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import tensorflow as tf

# Define the feature description dictionary
feature_description = {
    'feature1': tf.io.FixedLenFeature([], tf.float32),
    'feature2': tf.io.FixedLenFeature([], tf.int64),
    'feature3': tf.io.FixedLenFeature([], tf.string),
}

# Define the summary string
summary_string = b"serialized_summary_string_here"

# Parse the summary string
parsed_summary = tf.io.parse_single_example(summary_string, feature_description)

# Access the decoded features
feature1 = parsed_summary['feature1'].numpy()
feature2 = parsed_summary['feature2'].numpy()
feature3 = parsed_summary['feature3'].numpy()

print(feature1, feature2, feature3)

In this code snippet, you need to define the feature description dictionary that maps the feature names to their corresponding data types. Then, you can use the tf.io.parse_single_example function to parse the summary string using the feature description dictionary. Finally, you can access the decoded features by accessing the values in the parsed_summary dictionary.

Please note that you need to replace 'serialized_summary_string_here' with the actual serialized summary string that you want to decode.