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Allow SD attend and excite pipeline to work with any size output images #2835

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merged 1 commit into from
Apr 13, 2023
Merged

Allow SD attend and excite pipeline to work with any size output images #2835

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18 changes: 10 additions & 8 deletions src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_attend_and_excite.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@

import inspect
import math
from typing import Any, Callable, Dict, List, Optional, Union
from typing import Any, Callable, Dict, List, Optional, Tuple, Union

import numpy as np
import torch
Expand Down Expand Up @@ -75,7 +75,7 @@ def get_empty_store():

def __call__(self, attn, is_cross: bool, place_in_unet: str):
if self.cur_att_layer >= 0 and is_cross:
if attn.shape[1] == self.attn_res**2:
if attn.shape[1] == np.prod(self.attn_res):
self.step_store[place_in_unet].append(attn)

self.cur_att_layer += 1
Expand All @@ -97,7 +97,7 @@ def aggregate_attention(self, from_where: List[str]) -> torch.Tensor:
attention_maps = self.get_average_attention()
for location in from_where:
for item in attention_maps[location]:
cross_maps = item.reshape(-1, self.attn_res, self.attn_res, item.shape[-1])
cross_maps = item.reshape(-1, self.attn_res[0], self.attn_res[1], item.shape[-1])
out.append(cross_maps)
out = torch.cat(out, dim=0)
out = out.sum(0) / out.shape[0]
Expand All @@ -108,7 +108,7 @@ def reset(self):
self.step_store = self.get_empty_store()
self.attention_store = {}

def __init__(self, attn_res=16):
def __init__(self, attn_res):
"""
Initialize an empty AttentionStore :param step_index: used to visualize only a specific step in the diffusion
process
Expand Down Expand Up @@ -715,7 +715,7 @@ def __call__(
max_iter_to_alter: int = 25,
thresholds: dict = {0: 0.05, 10: 0.5, 20: 0.8},
scale_factor: int = 20,
attn_res: int = 16,
attn_res: Optional[Tuple[int]] = None,
):
r"""
Function invoked when calling the pipeline for generation.
Expand Down Expand Up @@ -787,8 +787,8 @@ def __call__(
Dictionary defining the iterations and desired thresholds to apply iterative latent refinement in.
scale_factor (`int`, *optional*, default to 20):
Scale factor that controls the step size of each Attend and Excite update.
attn_res (`int`, *optional*, default to 16):
The resolution of most semantic attention map.
attn_res (`tuple`, *optional*, default computed from width and height):
The 2D resolution of the semantic attention map.

Examples:

Expand Down Expand Up @@ -861,7 +861,9 @@ def __call__(
# 6. Prepare extra step kwargs. TODO: Logic should ideally just be moved out of the pipeline
extra_step_kwargs = self.prepare_extra_step_kwargs(generator, eta)

self.attention_store = AttentionStore(attn_res=attn_res)
if attn_res is None:
attn_res = int(np.ceil(width / 32)), int(np.ceil(height / 32))
self.attention_store = AttentionStore(attn_res)
self.register_attention_control()

# default config for step size from original repo
Expand Down