How to set batch size when inference with tensorflow?

@denis 

To set batch size when inferring with TensorFlow, you can use the batch_size parameter in the predict method of the model. Here is an example:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13

import tensorflow as tf

# Create the model
model = tf.keras.models.load_model('path/to/your/model.h5')

# Set the batch size
batch_size = 32

# Load your data
data = # Load your data here

# Make predictions with the specified batch size
predictions = model.predict(data, batch_size=batch_size)

In this example, the batch_size parameter is set to 32 in the predict method of the model. This will process the data in batches of 32 during inference. You can adjust the batch size based on your specific requirements and resources.