A small question about the requirement for Ram/VRam

[brbisheng]

Hello, Xavier, this is a brilliant contribution, thank you very much.

I encountered a small issue:
When running run_gradio_demo.py,
my process kept on being stopped without explicit error message (as below).

such as:

...
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.
DiffusionWrapper has 865.91 M params.
making attention of type 'vanilla-xformers' with 512 in_channels
building MemoryEfficientAttnBlock with 512 in_channels...
Working with z of shape (1, 4, 16, 16) = 1024 dimensions.
making attention of type 'vanilla-xformers' with 512 in_channels
building MemoryEfficientAttnBlock with 512 in_channels...
^C

Is it potentially because my system ram is too low (12G)?
when monitoring the process, I noticed that during the cross-attention phase, my CPU ram is hitting its upper limit 12G, but the GPU Vram is almost nil.

Could you provide some suggestions for potential causes of such an issue? ❤

[XavierCHEN34]

This might be caused by the mask refinement module, you could set the default as False
reference_mask_refine = gr.Checkbox(label='Reference Mask Refine', value=False, interactive = True)

[brbisheng]

Thank you very much, Xavier.

I checked the corresponding line and experimented with the default value, but the problem persisted.

I tried to trace the problem, it appears that I am not able to finish the following line

model = create_model(model_config ).cpu()

more precisely, my system fails loading the instaniate_from_config function,

def instantiate_from_config(config):
    if not "target" in config:
        if config == '__is_first_stage__':
            return None
        elif config == "__is_unconditional__":
            return None
        raise KeyError("Expected key `target` to instantiate.")
    return get_obj_from_str(config["target"])(**config.get("params", dict()))


def get_obj_from_str(string, reload=False):
    module, cls = string.rsplit(".", 1)
    if reload:
        module_imp = importlib.import_module(module)
        importlib.reload(module_imp)
    return getattr(importlib.import_module(module, package=None), cls)

[bbytiger]

running into a similar issue as above