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[Docs] Update TGATE in section optimization. #7698

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Apr 17, 2024
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[Docs] Update TGATE in section optimization. #7698

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13 changes: 8 additions & 5 deletions docs/source/en/optimization/tgate.md
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Original file line number Diff line number Diff line change
Expand Up @@ -35,10 +35,13 @@ from diffusers import PixArtAlphaPipeline
from tgate import TgatePixArtLoader

pipe = PixArtAlphaPipeline.from_pretrained("PixArt-alpha/PixArt-XL-2-1024-MS", torch_dtype=torch.float16)

gate_step = 8
inference_step = 25
pipe = TgatePixArtLoader(
pipe,
gate_step=8,
num_inference_steps=25,
gate_step=gate_step,
num_inference_steps=inference_step,
).to("cuda")

image = pipe.tgate(
Expand All @@ -56,6 +59,7 @@ Accelerate `StableDiffusionXLPipeline` with T-GATE:
import torch
from diffusers import StableDiffusionXLPipeline
from diffusers import DPMSolverMultistepScheduler
from tgate import TgateSDXLLoader

pipe = StableDiffusionXLPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
Expand All @@ -65,7 +69,6 @@ pipe = StableDiffusionXLPipeline.from_pretrained(
)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)

from tgate import TgateSDXLLoader
gate_step = 10
inference_step = 25
pipe = TgateSDXLLoader(
Expand All @@ -89,6 +92,7 @@ Accelerate `StableDiffusionXLPipeline` with [DeepCache](https://github.com/horse
import torch
from diffusers import StableDiffusionXLPipeline
from diffusers import DPMSolverMultistepScheduler
from tgate import TgateSDXLDeepCacheLoader

pipe = StableDiffusionXLPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
Expand All @@ -98,7 +102,6 @@ pipe = StableDiffusionXLPipeline.from_pretrained(
)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)

from tgate import TgateSDXLDeepCacheLoader
gate_step = 10
inference_step = 25
pipe = TgateSDXLDeepCacheLoader(
Expand All @@ -123,6 +126,7 @@ import torch
from diffusers import StableDiffusionXLPipeline
from diffusers import UNet2DConditionModel, LCMScheduler
from diffusers import DPMSolverMultistepScheduler
from tgate import TgateSDXLLoader

unet = UNet2DConditionModel.from_pretrained(
"latent-consistency/lcm-sdxl",
Expand All @@ -137,7 +141,6 @@ pipe = StableDiffusionXLPipeline.from_pretrained(
)
pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)

from tgate import TgateSDXLLoader
gate_step = 1
inference_step = 4
pipe = TgateSDXLLoader(
Expand Down