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Update pipelines/pipeline_seesr.py
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pipelines/pipeline_seesr.py
CHANGED
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@@ -1031,6 +1031,7 @@ class StableDiffusionControlNetPipeline(DiffusionPipeline, TextualInversionLoade
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# 2) now repeat latents/images/prompts
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latents = latents.repeat_interleave(num_particles, dim=0)
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image = image.repeat_interleave(num_particles, dim=0)
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prompt_embeds = prompt_embeds.repeat_interleave(num_particles, dim=0)
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latents.requires_grad_(True)
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@@ -1070,7 +1071,7 @@ class StableDiffusionControlNetPipeline(DiffusionPipeline, TextualInversionLoade
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if h*w<=tile_size*tile_size: # tiled latent input
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down_block_res_samples, mid_block_res_sample = [None]*10, None
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print(f"controlnet 1 started with {controlnet_latent_model_input.shape}:{
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down_block_res_samples, mid_block_res_sample = self.controlnet(
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controlnet_latent_model_input,
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# 2) now repeat latents/images/prompts
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latents = latents.repeat_interleave(num_particles, dim=0)
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image = image.repeat_interleave(num_particles, dim=0)
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ram_encoder_hidden_states = ram_encoder_hidden_states.repeat_interleave(num_particles, dim=0)
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prompt_embeds = prompt_embeds.repeat_interleave(num_particles, dim=0)
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latents.requires_grad_(True)
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if h*w<=tile_size*tile_size: # tiled latent input
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down_block_res_samples, mid_block_res_sample = [None]*10, None
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print(f"controlnet 1 started with {controlnet_latent_model_input.shape}:{ram_encoder_hidden_states.shape}")
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down_block_res_samples, mid_block_res_sample = self.controlnet(
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controlnet_latent_model_input,
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