ComfyUI Node: Text Scheduler 🍌

Text Scheduler 🍌| Text Scheduler 🍌:

The TextScheduler| Text Scheduler 🍌 node is designed to facilitate the generation of sigma values based on a custom sequence of timesteps provided as a text input. This node is particularly useful for AI artists who need precise control over the sigma values used in their models' sampling processes. By allowing you to input a comma-separated list of timesteps, the TextScheduler| Text Scheduler 🍌 node converts these into sigma values that can be used to influence the behavior of your model's sampling mechanism. This flexibility can help you achieve more refined and customized results in your AI-generated art.

Text Scheduler 🍌| Text Scheduler 🍌 Input Parameters:

model

This parameter expects a model object that contains the sampling mechanism. The model is used to compute the sigma values based on the provided timesteps. The model should be compatible with the node's requirements to ensure accurate sigma generation.

timesteps

This parameter takes a string input, which should be a comma-separated list of timesteps (e.g., "999,893,...,156"). These timesteps are converted into sigma values that guide the sampling process. The input string can be multiline, allowing for more complex sequences. The timesteps should be provided in a format that the model can interpret correctly.

verbose

This boolean parameter controls whether detailed information about the generated sigma values is printed to the console. If set to true, the node will output the list of sigma values, which can be useful for debugging and fine-tuning your input parameters. The default value is false.

Text Scheduler 🍌| Text Scheduler 🍌 Output Parameters:

SIGMAS

The output of this node is a tensor of sigma values, which are derived from the provided timesteps. These sigma values are crucial for the sampling process in your model, as they influence the noise levels and overall behavior of the generated outputs. The sigma values are returned as a single tensor, with an additional zero appended to the end to signify the end of the sequence.

Text Scheduler 🍌| Text Scheduler 🍌 Usage Tips:

• Ensure that the timesteps string is correctly formatted and free of spaces to avoid parsing errors.
• Use the verbose option to print the sigma values and verify that they match your expectations.
• Experiment with different sequences of timesteps to see how they affect the output of your model, allowing you to fine-tune the results.

Text Scheduler 🍌| Text Scheduler 🍌 Common Errors and Solutions:

ValueError: could not convert string to float

• Explanation: This error occurs when the timesteps string contains non-numeric values or is improperly formatted.
• Solution: Double-check the timesteps string to ensure it only contains numeric values separated by commas, with no extra spaces or characters.

AttributeError: 'NoneType' object has no attribute 'model_sampling'

• Explanation: This error indicates that the provided model object does not have the required sampling mechanism.
• Solution: Verify that the model object is correctly initialized and compatible with the TextScheduler| Text Scheduler 🍌 node's requirements.

TypeError: 'NoneType' object is not iterable

• Explanation: This error can occur if the timesteps string is empty or improperly formatted.
• Solution: Ensure that the timesteps string is not empty and follows the correct format of comma-separated numeric values.