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[sd3] make sure height and size are divisible by 16 #9573

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merged 2 commits into from
Oct 3, 2024
Merged

[sd3] make sure height and size are divisible by 16 #9573

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yiyixuxu Oct 2, 2024
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yiyixuxu Oct 2, 2024
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13 changes: 11 additions & 2 deletions src/diffusers/pipelines/controlnet_sd3/pipeline_stable_diffusion_3_controlnet_inpainting.py
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Original file line number Diff line number Diff line change
Expand Up @@ -251,6 +251,9 @@ def __init__(
if hasattr(self, "transformer") and self.transformer is not None
else 128
)
self.patch_size = (
self.transformer.config.patch_size if hasattr(self, "transformer") and self.transformer is not None else 2
)

# Copied from diffusers.pipelines.stable_diffusion_3.pipeline_stable_diffusion_3.StableDiffusion3Pipeline._get_t5_prompt_embeds
def _get_t5_prompt_embeds(
Expand Down Expand Up @@ -577,8 +580,14 @@ def check_inputs(
callback_on_step_end_tensor_inputs=None,
max_sequence_length=None,
):
if height % 8 != 0 or width % 8 != 0:
raise ValueError(f"`height` and `width` have to be divisible by 8 but are {height} and {width}.")
if (
height % (self.vae_scale_factor * self.patch_size) != 0
or width % (self.vae_scale_factor * self.patch_size) != 0
):
raise ValueError(
f"`height` and `width` have to be divisible by {self.vae_scale_factor * self.patch_size} but are {height} and {width}."
f"You can use height {height - height % (self.vae_scale_factor * self.patch_size)} and width {width - width % (self.vae_scale_factor * self.patch_size)}."
)

if callback_on_step_end_tensor_inputs is not None and not all(
k in self._callback_tensor_inputs for k in callback_on_step_end_tensor_inputs
Expand Down
13 changes: 11 additions & 2 deletions src/diffusers/pipelines/pag/pipeline_pag_sd_3.py
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Original file line number Diff line number Diff line change
Expand Up @@ -212,6 +212,9 @@ def __init__(
if hasattr(self, "transformer") and self.transformer is not None
else 128
)
self.patch_size = (
self.transformer.config.patch_size if hasattr(self, "transformer") and self.transformer is not None else 2
)

self.set_pag_applied_layers(
pag_applied_layers, pag_attn_processors=(PAGCFGJointAttnProcessor2_0(), PAGJointAttnProcessor2_0())
Expand Down Expand Up @@ -542,8 +545,14 @@ def check_inputs(
callback_on_step_end_tensor_inputs=None,
max_sequence_length=None,
):
if height % 8 != 0 or width % 8 != 0:
raise ValueError(f"`height` and `width` have to be divisible by 8 but are {height} and {width}.")
if (
height % (self.vae_scale_factor * self.patch_size) != 0
or width % (self.vae_scale_factor * self.patch_size) != 0
):
raise ValueError(
f"`height` and `width` have to be divisible by {self.vae_scale_factor * self.patch_size} but are {height} and {width}."
f"You can use height {height - height % (self.vae_scale_factor * self.patch_size)} and width {width - width % (self.vae_scale_factor * self.patch_size)}."
)

if callback_on_step_end_tensor_inputs is not None and not all(
k in self._callback_tensor_inputs for k in callback_on_step_end_tensor_inputs
Expand Down
13 changes: 11 additions & 2 deletions src/diffusers/pipelines/stable_diffusion_3/pipeline_stable_diffusion_3.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -203,6 +203,9 @@ def __init__(
if hasattr(self, "transformer") and self.transformer is not None
else 128
)
self.patch_size = (
self.transformer.config.patch_size if hasattr(self, "transformer") and self.transformer is not None else 2
)

def _get_t5_prompt_embeds(
self,
Expand Down Expand Up @@ -525,8 +528,14 @@ def check_inputs(
callback_on_step_end_tensor_inputs=None,
max_sequence_length=None,
):
if height % 8 != 0 or width % 8 != 0:
raise ValueError(f"`height` and `width` have to be divisible by 8 but are {height} and {width}.")
if (
height % (self.vae_scale_factor * self.patch_size) != 0
or width % (self.vae_scale_factor * self.patch_size) != 0
):
raise ValueError(
f"`height` and `width` have to be divisible by {self.vae_scale_factor * self.patch_size} but are {height} and {width}."
f"You can use height {height - height % (self.vae_scale_factor * self.patch_size)} and width {width - width % (self.vae_scale_factor * self.patch_size)}."
)

if callback_on_step_end_tensor_inputs is not None and not all(
k in self._callback_tensor_inputs for k in callback_on_step_end_tensor_inputs
Expand Down
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