better sampler

modules_forge/forge_sampler.py

@@ -0,0 +1,49 @@
+import torch
+from ldm_patched.modules.conds import CONDRegular, CONDCrossAttn
+from ldm_patched.modules.samplers import sampling_function
+
+
+def cond_from_a1111_to_patched_ldm(cond):
+    if isinstance(cond, torch.Tensor):
+        result = dict(
+            cross_attn=cond,
+            model_conds=dict(
+                c_crossattn=CONDCrossAttn(cond),
+            )
+        )
+        return [result, ]
+
+    cross_attn = cond['crossattn']
+    pooled_output = cond['vector']
+
+    result = dict(
+        cross_attn=cross_attn,
+        pooled_output=pooled_output,
+        model_conds=dict(
+            c_crossattn=CONDCrossAttn(cross_attn),
+            y=CONDRegular(pooled_output)
+        )
+    )
+
+    return [result, ]
+
+
+def forge_sample(self, denoiser_params, cond_scale):
+    model = self.inner_model.inner_model.forge_objects.unet.model
+    x = denoiser_params.x
+    timestep = denoiser_params.sigma
+    uncond = cond_from_a1111_to_patched_ldm(denoiser_params.text_uncond)
+    cond = cond_from_a1111_to_patched_ldm(denoiser_params.text_cond)
+    model_options = self.inner_model.inner_model.forge_objects.unet.model_options
+    seed = self.p.seeds[0]
+
+    image_cond_in = denoiser_params.image_cond
+    if isinstance(image_cond_in, torch.Tensor):
+        if image_cond_in.shape[0] == x.shape[0] \
+                and image_cond_in.shape[2] == x.shape[2] \
+                and image_cond_in.shape[3] == x.shape[3]:
+            uncond[0]['model_conds']['c_concat'] = CONDRegular(image_cond_in)
+            cond[0]['model_conds']['c_concat'] = CONDRegular(image_cond_in)
+
+    denoised = sampling_function(model, x, timestep, uncond, cond, cond_scale, model_options, seed)
+    return denoised