From ded26d1fbc5e56fc71938028626f3bed96e2cdbe Mon Sep 17 00:00:00 2001
From: Vladimir Mandic <mandic00@live.com>
Date: Sun, 24 May 2026 08:45:41 +0200
Subject: [PATCH] lens fixes

Signed-off-by: Vladimir Mandic <mandic00@live.com>
---
 TODO.md                        |  2 +-
 pipelines/lens/pipeline.py     |  6 +++---
 pipelines/lens/text_encoder.py | 12 +++++++++---
 pipelines/model_lens.py        |  6 ++----
 ui/imageViewer.ts              |  2 +-
 5 files changed, 16 insertions(+), 12 deletions(-)

diff --git a/TODO.md b/TODO.md
index 5bed4d485..bcb8c536a 100644
--- a/TODO.md
+++ b/TODO.md
@@ -4,7 +4,6 @@
 
 - Inpaint: https://discord.com/channels/1101998836328697867/1130536562422186044/1506850651035144322
 - Torch lazy-load
-- pnpm-vs-npm
 
 ## Features
 
@@ -13,6 +12,7 @@
 - Chat-based interface, @vladmandic
 - Control tab verify overrides handling, @vladmandic
 - Reimplement `llama` remover for Kanvas, @vladmandic
+  Object clear: https://huggingface.co/jixin0101/ObjectClear
 
 - Detailer postprocessing, @CalamitousFelicitousness
 - Cloud providers, @CalamitousFelicitousness
diff --git a/pipelines/lens/pipeline.py b/pipelines/lens/pipeline.py
index c167b5312..051269b82 100644
--- a/pipelines/lens/pipeline.py
+++ b/pipelines/lens/pipeline.py
@@ -131,7 +131,8 @@ class LensPipeline(DiffusionPipeline):
         text_encoder: LensGptOssEncoder,
         tokenizer: PreTrainedTokenizerBase,
         transformer: LensTransformer2DModel,
-        reasoner: Optional[PromptReasoner] = True,
+        reasoner: Optional[PromptReasoner] = None,
+        use_reasoner=False,
     ) -> None:
         super().__init__()
         self.register_modules(
@@ -156,7 +157,7 @@ class LensPipeline(DiffusionPipeline):
                 self.transformer.config.selected_layer_index
             )
 
-        if reasoner is not None:
+        if use_reasoner and reasoner is None:
             self.reasoner = PromptReasoner(
                 text_encoder=self.text_encoder, tokenizer=self.tokenizer
             )
@@ -296,7 +297,6 @@ class LensPipeline(DiffusionPipeline):
     ) -> List[str]:
         if self.reasoner is None:
             return list(prompts)
-        print('HERE REFINE')
         return self.reasoner.refine(prompts, enable=enable_reasoner)
 
     # ------------------------------------------------------------------
diff --git a/pipelines/lens/text_encoder.py b/pipelines/lens/text_encoder.py
index 0b16410e4..d5d3bc63d 100644
--- a/pipelines/lens/text_encoder.py
+++ b/pipelines/lens/text_encoder.py
@@ -38,11 +38,11 @@ class LensGptOssEncoder(GptOssForCausalLM):
                 f"layer_indices out of range; got {layers}, "
                 f"model has {len(self.model.layers)} layers"
             )
-        self._lens_selected_layers = layers
-        self._lens_max_layer = max(layers)
+        self._lens_selected_layers = layers # pylint: disable=attribute-defined-outside-init
+        self._lens_max_layer = max(layers) # pylint: disable=attribute-defined-outside-init
 
     @torch.no_grad()
-    def forward(  # type: ignore[override]
+    def forward(  # type: ignore[override] # pylint: keyword-arg-before-vararg
         self,
         input_ids: Optional[torch.LongTensor] = None,
         attention_mask: Optional[torch.Tensor] = None,
@@ -78,6 +78,12 @@ class LensGptOssEncoder(GptOssForCausalLM):
 
         model = self.model
         inputs_embeds = model.embed_tokens(input_ids)
+        target_dtype = inputs_embeds.dtype
+        if len(model.layers) > 0:
+            target_dtype = model.layers[0].self_attn.k_proj.weight.dtype
+        if inputs_embeds.dtype != target_dtype:
+            inputs_embeds = inputs_embeds.to(dtype=target_dtype)
+
         position_ids = torch.arange(
             inputs_embeds.shape[1], device=inputs_embeds.device
         ).unsqueeze(0).expand_as(input_ids)
diff --git a/pipelines/model_lens.py b/pipelines/model_lens.py
index 8c422eb7d..60f340f4d 100644
--- a/pipelines/model_lens.py
+++ b/pipelines/model_lens.py
@@ -11,16 +11,14 @@ def load_lens(checkpoint_info, diffusers_load_config=None):
     sd_models.hf_auth_check(checkpoint_info)
 
     load_args, _quant_args = model_quant.get_dit_args(diffusers_load_config, allow_quant=False)
-    log.debug(f'Load model: type=Lens repo="{repo_id}" config={diffusers_load_config} offload={shared.opts.diffusers_offload_mode} dtype={devices.dtype} args={load_args}')
+    log.debug(f'Load model: type=Lens repo="{repo_id}" config={diffusers_load_config} offload={shared.opts.diffusers_offload_mode} dtype={devices.dtype} reasoner={shared.opts.model_lens_enable_pe} args={load_args}')
 
     from pipelines import lens
 
     transformer = generic.load_transformer(repo_id, cls_name=lens.LensTransformer2DModel, load_config=diffusers_load_config)
     text_encoder = generic.load_text_encoder(repo_id, cls_name=lens.LensGptOssEncoder, load_config=diffusers_load_config, allow_quant=False) # te is prequantized using mxfp4
 
-    if not shared.opts.model_lens_enable_pe:
-        load_args['reasoner'] = None
-
+    load_args['use_reasoner'] = shared.opts.model_lens_enable_pe
     pipe = lens.LensPipeline.from_pretrained(
         repo_id,
         transformer=transformer,
diff --git a/ui/imageViewer.ts b/ui/imageViewer.ts
index 63eea1ffd..1891ced6e 100644
--- a/ui/imageViewer.ts
+++ b/ui/imageViewer.ts
@@ -125,7 +125,6 @@ export async function getExif(el) {
   // let html = `<b>Image</b> <a href="${el.src}" target="_blank">${el.src}</a> <b>Size</b> ${el.naturalWidth}x${el.naturalHeight}<br>`;
   let html = '';
   let params;
-  debug('getExif', exif);
   if (exif.parameters) {
     params = exif.parameters;
   } else if (exif.userComment) {
@@ -133,6 +132,7 @@ export async function getExif(el) {
   } else {
     params = '';
   }
+  debug('getExif', params);
   if (params.length > 0) html += `<b>Prompt</b> ${params || ''}<br>`;
   html = html.replace('Negative prompt:', '<br><b>Negative</b>');
   html = html.replace('Steps:', '<br><b>Params</b> Steps:');