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[test][DO NOT MERGE] disable fori_loop #11

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[test][DO NOT MERGE] disable fori_loop #11

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6b1559b
disable fori_loop in generate_sdxl.py
ManfeiBai Mar 21, 2024
f266883
Update generate.py
ManfeiBai Mar 21, 2024
0d4805e
Update pipeline_flax_stable_diffusion_xl.py
ManfeiBai Mar 21, 2024
58c7783
Update pipeline_flax_stable_diffusion.py
ManfeiBai Mar 21, 2024
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6 changes: 4 additions & 2 deletions src/maxdiffusion/generate.py
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Original file line number Diff line number Diff line change
Expand Up @@ -168,8 +168,10 @@ def run_inference(unet_state, vae_state, params, rng, config, batch_size, pipeli
vae_decode_p = functools.partial(vae_decode, pipeline=pipeline)

with mesh, nn_partitioning.axis_rules(config.logical_axis_rules):
latents, _, _ = jax.lax.fori_loop(0, config.num_inference_steps,
loop_body_p, (latents, scheduler_state, unet_state))
val = (latents, scheduler_state, unet_state)
for i in range(0, config.num_inference_steps):
val = loop_body_p(i, val)
latents, _, _ = val
image = vae_decode_p(latents, vae_state)
return image

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6 changes: 4 additions & 2 deletions src/maxdiffusion/generate_sdxl.py
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Original file line number Diff line number Diff line change
Expand Up @@ -226,8 +226,10 @@ def run_inference(unet_state, vae_state, params, rng, config, batch_size, pipeli
vae_decode_p = functools.partial(vae_decode, pipeline=pipeline)

with mesh, nn_partitioning.axis_rules(config.logical_axis_rules):
latents, _, _ = jax.lax.fori_loop(0, config.num_inference_steps,
loop_body_p, (latents, scheduler_state, unet_state))
val = (latents, scheduler_state, unet_state)
for i in range(0, config.num_inference_steps):
val = loop_body_p(i, val)
latents, _, _ = val
image = vae_decode_p(latents, vae_state)
return image

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5 changes: 4 additions & 1 deletion src/maxdiffusion/pipelines/stable_diffusion/pipeline_flax_stable_diffusion.py
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Original file line number Diff line number Diff line change
Expand Up @@ -299,7 +299,10 @@ def loop_body(step, args):
for i in range(num_inference_steps):
latents, scheduler_state = loop_body(i, (latents, scheduler_state))
else:
latents, _ = jax.lax.fori_loop(0, num_inference_steps, loop_body, (latents, scheduler_state))
val = (latents, scheduler_state)
for i in range(0, num_inference_steps):
val = loop_body(i, val)
latents, _ = val

# scale and decode the image latents with vae
latents = 1 / self.vae.config.scaling_factor * latents
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5 changes: 4 additions & 1 deletion src/maxdiffusion/pipelines/stable_diffusion_xl/pipeline_flax_stable_diffusion_xl.py
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Expand Up @@ -261,7 +261,10 @@ def loop_body(step, args):
for i in range(num_inference_steps):
latents, scheduler_state = loop_body(i, (latents, scheduler_state))
else:
latents, _ = jax.lax.fori_loop(0, num_inference_steps, loop_body, (latents, scheduler_state))
val = (latents, scheduler_state)
for i in range(0, num_inference_steps):
val = loop_body(i, val)
latents, _ = val

if return_latents:
return latents
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