ComfyUI Node: 🔧 SDXL Empty Latent Size Picker

🔧 SDXL Empty Latent Size Picker+:

The SDXLEmptyLatentSizePicker+ node is designed to generate an empty latent tensor with a specified resolution and batch size, which is essential for various AI art generation tasks. This node allows you to select from a range of predefined resolutions, making it easier to match the latent tensor size to your specific needs. By providing a batch size parameter, it also supports the creation of multiple latent tensors simultaneously, which can be useful for batch processing or generating multiple variations of an artwork. The primary goal of this node is to facilitate the initialization of latent tensors that can be further processed or manipulated in your AI art pipeline.

🔧 SDXL Empty Latent Size Picker+ Input Parameters:

resolution

The resolution parameter allows you to select the desired resolution for the latent tensor. It offers a list of predefined resolutions, each associated with a scaling factor. The resolution is specified in the format width x height (scale_factor), where width and height are the dimensions of the tensor. The default value is 1024x1024 (1.0). This parameter impacts the size of the generated latent tensor and should be chosen based on the requirements of your specific task.

batch_size

The batch_size parameter specifies the number of latent tensors to generate. It accepts an integer value with a default of 1, a minimum of 1, and a maximum of 4096. This parameter is crucial for batch processing, allowing you to create multiple latent tensors in a single execution, which can be useful for generating multiple variations or for parallel processing in your AI art workflow.

🔧 SDXL Empty Latent Size Picker+ Output Parameters:

LATENT

The LATENT output is a dictionary containing the generated latent tensor(s). The tensor is initialized with zeros and has dimensions based on the selected resolution and batch size. This output is essential for further processing in your AI art pipeline, serving as the starting point for various transformations and manipulations.

width

The width output provides the width of the generated latent tensor. This value is derived from the selected resolution and is returned as an integer. It is useful for downstream nodes that require knowledge of the tensor's dimensions for further processing.

height

The height output provides the height of the generated latent tensor. Similar to the width output, this value is derived from the selected resolution and is returned as an integer. It is important for ensuring compatibility with other nodes that process the latent tensor.

🔧 SDXL Empty Latent Size Picker+ Usage Tips:

• Select a resolution that matches the requirements of your AI art generation task to ensure optimal performance and compatibility with other nodes.
• Use the batch_size parameter to generate multiple latent tensors simultaneously, which can save time and resources when processing multiple images or variations.
• Ensure that the selected resolution and batch size do not exceed the memory capacity of your device to avoid runtime errors.

🔧 SDXL Empty Latent Size Picker+ Common Errors and Solutions:

RuntimeError: CUDA out of memory

• Explanation: This error occurs when the selected resolution and batch size exceed the available memory on your device.
• Solution: Reduce the resolution or batch size to fit within the memory limits of your device.

ValueError: Invalid resolution format

• Explanation: This error occurs when the resolution parameter is not in the expected format width x height (scale_factor).
• Solution: Ensure that the resolution is selected from the predefined list and follows the correct format.

TypeError: batch_size must be an integer

• Explanation: This error occurs when the batch_size parameter is not an integer.
• Solution: Ensure that the batch_size is specified as an integer value within the allowed range (1 to 4096).