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handle dict as pipeline result

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This commit is contained in:
Vladimir Mandic
2024-02-13 15:10:19 -05:00
parent ccd6c86c21
commit c16cd2eeec
4 changed files with 77 additions and 6 deletions
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modules/processing_diffusers.py
+7 -6
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@@ -1,3 +1,4 @@
from types import SimpleNamespace
import os
import time
import math
@@ -437,6 +438,8 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
try:
t0 = time.time()
output = shared.sd_model(**base_args) # pylint: disable=not-callable
if isinstance(output, dict):
output = SimpleNamespace(**output)
openvino_post_compile(op="base") # only executes on compiled vino models
if shared.cmd_opts.profile:
t1 = time.time()
@@ -446,9 +449,6 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
shared.log.debug(f'Generated: frames={output.frames[0].shape[1]}')
else:
shared.log.debug(f'Generated: frames={len(output.frames[0])}')
if isinstance(output, dict):
from types import SimpleNamespace
output = SimpleNamespace(**output)
output.images = output.frames[0]
if isinstance(output.images, np.ndarray):
output.images = torch.from_numpy(output.images)
@@ -512,6 +512,8 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
shared.state.sampling_steps = hires_args['num_inference_steps']
try:
output = shared.sd_model(**hires_args) # pylint: disable=not-callable
if isinstance(output, dict):
output = SimpleNamespace(**output)
openvino_post_compile(op="base")
except AssertionError as e:
shared.log.info(e)
@@ -570,6 +572,8 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
if 'requires_aesthetics_score' in shared.sd_refiner.config:
shared.sd_refiner.register_to_config(requires_aesthetics_score=shared.opts.diffusers_aesthetics_score)
refiner_output = shared.sd_refiner(**refiner_args) # pylint: disable=not-callable
if isinstance(refiner_output, dict):
refiner_output = SimpleNamespace(**refiner_output)
openvino_post_compile(op="refiner")
except AssertionError as e:
shared.log.info(e)
@@ -589,9 +593,6 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
# final decode since there is no refiner
if not is_refiner_enabled():
if output is not None:
if isinstance(output, dict):
from types import SimpleNamespace
output = SimpleNamespace(**output)
if not hasattr(output, 'images') and hasattr(output, 'frames'):
shared.log.debug(f'Generated: frames={len(output.frames[0])}')
output.images = output.frames[0]