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fix: typo in callback function name and property (#6834)
* fix: callback function name is incorrect On this tutorial there is a function defined and then used inside `callback_on_step_end` argument, but the name was not correct (mismatch) * fix: typo in num_timestep (correct is num_timesteps) fixed property name
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@@ -18,8 +18,8 @@ This guide will show you how to use the `callback_on_step_end` parameter to disa
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The callback function should have the following arguments:
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* `pipe` (or the pipeline instance) provides access to useful properties such as `num_timestep` and `guidance_scale`. You can modify these properties by updating the underlying attributes. For this example, you'll disable CFG by setting `pipe._guidance_scale=0.0`.
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* `step_index` and `timestep` tell you where you are in the denoising loop. Use `step_index` to turn off CFG after reaching 40% of `num_timestep`.
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* `pipe` (or the pipeline instance) provides access to useful properties such as `num_timesteps` and `guidance_scale`. You can modify these properties by updating the underlying attributes. For this example, you'll disable CFG by setting `pipe._guidance_scale=0.0`.
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* `step_index` and `timestep` tell you where you are in the denoising loop. Use `step_index` to turn off CFG after reaching 40% of `num_timesteps`.
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* `callback_kwargs` is a dict that contains tensor variables you can modify during the denoising loop. It only includes variables specified in the `callback_on_step_end_tensor_inputs` argument, which is passed to the pipeline's `__call__` method. Different pipelines may use different sets of variables, so please check a pipeline's `_callback_tensor_inputs` attribute for the list of variables you can modify. Some common variables include `latents` and `prompt_embeds`. For this function, change the batch size of `prompt_embeds` after setting `guidance_scale=0.0` in order for it to work properly.
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Your callback function should look something like this:
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@@ -27,7 +27,7 @@ Your callback function should look something like this:
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```python
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def callback_dynamic_cfg(pipe, step_index, timestep, callback_kwargs):
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# adjust the batch_size of prompt_embeds according to guidance_scale
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if step_index == int(pipe.num_timestep * 0.4):
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if step_index == int(pipe.num_timesteps * 0.4):
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prompt_embeds = callback_kwargs["prompt_embeds"]
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prompt_embeds = prompt_embeds.chunk(2)[-1]
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@@ -49,7 +49,7 @@ pipe = pipe.to("cuda")
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prompt = "a photo of an astronaut riding a horse on mars"
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generator = torch.Generator(device="cuda").manual_seed(1)
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out = pipe(prompt, generator=generator, callback_on_step_end=callback_custom_cfg, callback_on_step_end_tensor_inputs=['prompt_embeds'])
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out = pipe(prompt, generator=generator, callback_on_step_end=callback_dynamic_cfg, callback_on_step_end_tensor_inputs=['prompt_embeds'])
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out.images[0].save("out_custom_cfg.png")
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```
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