Fabrice-TIERCELIN commited on
Commit
f200691
1 Parent(s): da3b33e

Code out of GPU compute

Browse files
Files changed (1) hide show
  1. app.py +16 -14
app.py CHANGED
@@ -100,7 +100,7 @@ def stage2_process(*args, **kwargs):
100
  return restore_in_Xmin(*args, **kwargs)
101
  except Exception as e:
102
  print('Exception of type ' + str(type(e)))
103
- if type(e).__name__ == 'gradio.exceptions.Error':
104
  print('Exception of name ' + type(e).__name__)
105
  raise e
106
 
@@ -201,6 +201,12 @@ def restore_in_Xmin(
201
  input_height, input_width, input_channel = denoise_image.shape
202
  denoise_image = denoise_image.resize((input_width // downscale, input_height // downscale), Image.LANCZOS)
203
 
 
 
 
 
 
 
204
  # Allocation
205
  if allocation == 1:
206
  return restore_in_1min(
@@ -243,39 +249,39 @@ def restore_in_Xmin(
243
  noisy_image, denoise_image, prompt, a_prompt, n_prompt, num_samples, min_size, downscale, upscale, edm_steps, s_stage1, s_stage2, s_cfg, randomize_seed, seed, s_churn, s_noise, color_fix_type, diff_dtype, ae_dtype, gamma_correction, linear_CFG, linear_s_stage2, spt_linear_CFG, spt_linear_s_stage2, model_select, output_format, allocation
244
  )
245
 
246
- @spaces.GPU(duration=60)
247
  def restore_in_1min(*args, **kwargs):
248
  return restore(*args, **kwargs)
249
 
250
- @spaces.GPU(duration=120)
251
  def restore_in_2min(*args, **kwargs):
252
  return restore(*args, **kwargs)
253
 
254
- @spaces.GPU(duration=180)
255
  def restore_in_3min(*args, **kwargs):
256
  return restore(*args, **kwargs)
257
 
258
- @spaces.GPU(duration=240)
259
  def restore_in_4min(*args, **kwargs):
260
  return restore(*args, **kwargs)
261
 
262
- @spaces.GPU(duration=300)
263
  def restore_in_5min(*args, **kwargs):
264
  return restore(*args, **kwargs)
265
 
266
- @spaces.GPU(duration=360)
267
  def restore_in_6min(*args, **kwargs):
268
  return restore(*args, **kwargs)
269
 
270
- @spaces.GPU(duration=420)
271
  def restore_in_7min(*args, **kwargs):
272
  return restore(*args, **kwargs)
273
 
274
- @spaces.GPU(duration=480)
275
  def restore_in_8min(*args, **kwargs):
276
  return restore(*args, **kwargs)
277
 
278
- @spaces.GPU(duration=540)
279
  def restore_in_9min(*args, **kwargs):
280
  return restore(*args, **kwargs)
281
 
@@ -316,9 +322,6 @@ def restore(
316
  start = time.time()
317
  print('restore ==>>')
318
 
319
- if torch.cuda.device_count() == 0:
320
- gr.Warning('Set this space to GPU config to make it work.')
321
- return [input_image] * 2, [input_image], None, None
322
  torch.cuda.set_device(SUPIR_device)
323
 
324
  if model_select != model.current_model:
@@ -328,7 +331,6 @@ def restore(
328
  elif model_select == 'v0-F':
329
  model.load_state_dict(ckpt_F, strict=False)
330
  model.current_model = model_select
331
- input_image = HWC3(np.array(input_image))
332
  input_image = upscale_image(input_image, upscale, unit_resolution=32,
333
  min_size=min_size)
334
 
 
100
  return restore_in_Xmin(*args, **kwargs)
101
  except Exception as e:
102
  print('Exception of type ' + str(type(e)))
103
+ if type(e).__name__ == "<class 'gradio.exceptions.Error'>":
104
  print('Exception of name ' + type(e).__name__)
105
  raise e
106
 
 
201
  input_height, input_width, input_channel = denoise_image.shape
202
  denoise_image = denoise_image.resize((input_width // downscale, input_height // downscale), Image.LANCZOS)
203
 
204
+ if torch.cuda.device_count() == 0:
205
+ gr.Warning('Set this space to GPU config to make it work.')
206
+ return [noisy_image, denoise_image], [denoise_image], None, None
207
+
208
+ denoise_image = HWC3(np.array(denoise_image))
209
+
210
  # Allocation
211
  if allocation == 1:
212
  return restore_in_1min(
 
249
  noisy_image, denoise_image, prompt, a_prompt, n_prompt, num_samples, min_size, downscale, upscale, edm_steps, s_stage1, s_stage2, s_cfg, randomize_seed, seed, s_churn, s_noise, color_fix_type, diff_dtype, ae_dtype, gamma_correction, linear_CFG, linear_s_stage2, spt_linear_CFG, spt_linear_s_stage2, model_select, output_format, allocation
250
  )
251
 
252
+ @spaces.GPU(duration=59)
253
  def restore_in_1min(*args, **kwargs):
254
  return restore(*args, **kwargs)
255
 
256
+ @spaces.GPU(duration=119)
257
  def restore_in_2min(*args, **kwargs):
258
  return restore(*args, **kwargs)
259
 
260
+ @spaces.GPU(duration=179)
261
  def restore_in_3min(*args, **kwargs):
262
  return restore(*args, **kwargs)
263
 
264
+ @spaces.GPU(duration=239)
265
  def restore_in_4min(*args, **kwargs):
266
  return restore(*args, **kwargs)
267
 
268
+ @spaces.GPU(duration=299)
269
  def restore_in_5min(*args, **kwargs):
270
  return restore(*args, **kwargs)
271
 
272
+ @spaces.GPU(duration=359)
273
  def restore_in_6min(*args, **kwargs):
274
  return restore(*args, **kwargs)
275
 
276
+ @spaces.GPU(duration=419)
277
  def restore_in_7min(*args, **kwargs):
278
  return restore(*args, **kwargs)
279
 
280
+ @spaces.GPU(duration=479)
281
  def restore_in_8min(*args, **kwargs):
282
  return restore(*args, **kwargs)
283
 
284
+ @spaces.GPU(duration=539)
285
  def restore_in_9min(*args, **kwargs):
286
  return restore(*args, **kwargs)
287
 
 
322
  start = time.time()
323
  print('restore ==>>')
324
 
 
 
 
325
  torch.cuda.set_device(SUPIR_device)
326
 
327
  if model_select != model.current_model:
 
331
  elif model_select == 'v0-F':
332
  model.load_state_dict(ckpt_F, strict=False)
333
  model.current_model = model_select
 
334
  input_image = upscale_image(input_image, upscale, unit_resolution=32,
335
  min_size=min_size)
336