get_session` is not available when using TensorFlow 2.0.

The get_session function is not available in TensorFlow 2.0. This function was used in TensorFlow 1.x to get the current TensorFlow session, but it has been deprecated and removed in TensorFlow 2.0. Instead, TensorFlow 2.0 uses eager execution by default, which eliminates the need for explicitly managing sessions.

In TensorFlow 2.0, you can directly execute operations and evaluate tensors without the need for a session. The eager execution mode allows for immediate evaluation and debugging of operations. You can simply call functions and operations directly without the need to explicitly manage sessions.

If you need to perform specific operations that require a session-like behavior, you can use the tf.function decorator to create a graph function. This allows you to define a function that can be compiled into a TensorFlow graph for improved performance. However, even in this case, you don't need to explicitly manage sessions.

Here's an example of how you can use TensorFlow 2.0 without the get_session function:

import tensorflow as tf

# Define your model and operations
model = tf.keras.Sequential([...])

# Create your input data
input_data = [...]

# Perform forward pass
output = model(input_data)

# Print the output
print(output)

In this example, we define a model using the tf.keras.Sequential API, create input data, and perform a forward pass to get the output. We can directly print the output without the need for a session.

I hope this helps! Let me know if you have any further questions.