Merge branch 'comfyanonymous:master' into feature/blockweights

README.md

@@ -83,7 +83,7 @@ Put your VAE in: models/vae
 
 At the time of writing this pytorch has issues with python versions higher than 3.10 so make sure your python/pip versions are 3.10.
 
-### AMD (Linux only)
+### AMD GPUs (Linux only)
 AMD users can install rocm and pytorch with pip if you don't have it already installed, this is the command to install the stable version:
 
 ```pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/rocm5.4.2```

comfy/samplers.py

@@ -211,7 +211,10 @@ def sampling_function(model_function, x, timestep, uncond, cond, cond_scale, con
 
         max_total_area = model_management.maximum_batch_area()
         cond, uncond = calc_cond_uncond_batch(model_function, cond, uncond, x, timestep, max_total_area, cond_concat, model_options)
-        return uncond + (cond - uncond) * cond_scale
+        if "sampler_cfg_function" in model_options:
+            return model_options["sampler_cfg_function"](cond, uncond, cond_scale)
+        else:
+            return uncond + (cond - uncond) * cond_scale
 
 
 class CompVisVDenoiser(k_diffusion_external.DiscreteVDDPMDenoiser):

comfy/sd.py

@@ -289,6 +289,9 @@ class ModelPatcher:
     def set_model_tomesd(self, ratio):
         self.model_options["transformer_options"]["tomesd"] = {"ratio": ratio}
 
+    def set_model_sampler_cfg_function(self, sampler_cfg_function):
+        self.model_options["sampler_cfg_function"] = sampler_cfg_function
+
     def model_dtype(self):
         return self.model.diffusion_model.dtype
 

nodes.py

@@ -586,6 +586,24 @@ class EmptyLatentImage:
         return ({"samples":latent}, )
 
 
+class LatentFromBatch:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { "samples": ("LATENT",),
+                              "batch_index": ("INT", {"default": 0, "min": 0, "max": 63}),
+                              }}
+    RETURN_TYPES = ("LATENT",)
+    FUNCTION = "rotate"
+
+    CATEGORY = "latent"
+
+    def rotate(self, samples, batch_index):
+        s = samples.copy()
+        s_in = samples["samples"]
+        batch_index = min(s_in.shape[0] - 1, batch_index)
+        s["samples"] = s_in[batch_index:batch_index + 1].clone()
+        s["batch_index"] = batch_index
+        return (s,)
 
 class LatentUpscale:
     upscale_methods = ["nearest-exact", "bilinear", "area"]
@@ -761,7 +779,14 @@ def common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive,
     if disable_noise:
         noise = torch.zeros(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, device="cpu")
     else:
-        noise = torch.randn(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, generator=torch.manual_seed(seed), device="cpu")
+        batch_index = 0
+        if "batch_index" in latent:
+            batch_index = latent["batch_index"]
+
+        generator = torch.manual_seed(seed)
+        for i in range(batch_index):
+            noise = torch.randn([1] + list(latent_image.size())[1:], dtype=latent_image.dtype, layout=latent_image.layout, generator=generator, device="cpu")
+        noise = torch.randn(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, generator=generator, device="cpu")
 
     if "noise_mask" in latent:
         noise_mask = latent['noise_mask']
@@ -1149,6 +1174,7 @@ NODE_CLASS_MAPPINGS = {
     "VAELoader": VAELoader,
     "EmptyLatentImage": EmptyLatentImage,
     "LatentUpscale": LatentUpscale,
+    "LatentFromBatch": LatentFromBatch,
     "SaveImage": SaveImage,
     "PreviewImage": PreviewImage,
     "LoadImage": LoadImage,

web/extensions/core/editAttention.js

@@ -0,0 +1,117 @@
+import { app } from "/scripts/app.js";
+
+// Allows you to edit the attention weight by holding ctrl (or cmd) and using the up/down arrow keys
+
+const id = "Comfy.EditAttention";
+app.registerExtension({
+name:id,
+    init() {
+        function incrementWeight(weight, delta) {
+            const floatWeight = parseFloat(weight);
+            if (isNaN(floatWeight)) return weight;
+            const newWeight = floatWeight + delta;
+            if (newWeight < 0) return "0";
+            return String(Number(newWeight.toFixed(10)));
+        }
+
+        function findNearestEnclosure(text, cursorPos) {
+            let start = cursorPos, end = cursorPos;
+            let openCount = 0, closeCount = 0;
+
+            // Find opening parenthesis before cursor
+            while (start >= 0) {
+                start--;
+                if (text[start] === "(" && openCount === closeCount) break;
+                if (text[start] === "(") openCount++;
+                if (text[start] === ")") closeCount++;
+            }
+            if (start < 0) return false;
+
+            openCount = 0;
+            closeCount = 0;
+
+            // Find closing parenthesis after cursor
+            while (end < text.length) {
+                if (text[end] === ")" && openCount === closeCount) break;
+                if (text[end] === "(") openCount++;
+                if (text[end] === ")") closeCount++;
+                end++;
+            }
+            if (end === text.length) return false;
+
+            return { start: start + 1, end: end };
+        }
+
+        function addWeightToParentheses(text) {
+            const parenRegex = /^\((.*)\)$/;
+            const parenMatch = text.match(parenRegex);
+
+            const floatRegex = /:([+-]?(\d*\.)?\d+([eE][+-]?\d+)?)/;
+            const floatMatch = text.match(floatRegex);
+
+            if (parenMatch && !floatMatch) {
+                return `(${parenMatch[1]}:1.0)`;
+            } else {
+                return text;
+            }
+        };
+
+        function editAttention(event) {
+            const inputField = event.composedPath()[0];
+            const delta = 0.025;
+
+            if (inputField.tagName !== "TEXTAREA") return;
+            if (!(event.key === "ArrowUp" || event.key === "ArrowDown")) return;
+            if (!event.ctrlKey && !event.metaKey) return;
+
+            event.preventDefault();
+
+            let start = inputField.selectionStart;
+            let end = inputField.selectionEnd;
+            let selectedText = inputField.value.substring(start, end);
+
+            // If there is no selection, attempt to find the nearest enclosure
+            if (!selectedText) {
+                const nearestEnclosure = findNearestEnclosure(inputField.value, start);
+                if (nearestEnclosure) {
+                    start = nearestEnclosure.start;
+                    end = nearestEnclosure.end;
+                    selectedText = inputField.value.substring(start, end);
+                } else {
+                    return;
+                }
+            }
+
+            // If the selection ends with a space, remove it
+            if (selectedText[selectedText.length - 1] === " ") {
+                selectedText = selectedText.substring(0, selectedText.length - 1);
+                end -= 1;
+            }
+
+            // If there are parentheses left and right of the selection, select them
+            if (inputField.value[start - 1] === "(" && inputField.value[end] === ")") {
+                start -= 1;
+                end += 1;
+                selectedText = inputField.value.substring(start, end);
+            }
+
+            // If the selection is not enclosed in parentheses, add them
+            if (selectedText[0] !== "(" || selectedText[selectedText.length - 1] !== ")") {
+                console.log("adding parentheses", inputField.value[start], inputField.value[end], selectedText);
+                selectedText = `(${selectedText})`;
+            }
+
+            // If the selection does not have a weight, add a weight of 1.0
+            selectedText = addWeightToParentheses(selectedText);
+
+            // Increment the weight
+            const weightDelta = event.key === "ArrowUp" ? delta : -delta;
+            const updatedText = selectedText.replace(/(.*:)(\d+(\.\d+)?)(.*)/, (match, prefix, weight, _, suffix) => {
+              return prefix + incrementWeight(weight, weightDelta) + suffix;
+            });
+
+            inputField.setRangeText(updatedText, start, end, "select");
+        }
+        window.addEventListener("keydown", editAttention);
+    },
+});

web/extensions/core/keybinds.js

@@ -5,12 +5,6 @@ app.registerExtension({
 	name: id,
 	init() {
 		const keybindListener = function(event) {
-			const target = event.composedPath()[0];
-
-			if (target.tagName === "INPUT" || target.tagName === "TEXTAREA") {
-				return;
-			}
-
 			const modifierPressed = event.ctrlKey || event.metaKey;
 
 			// Queue prompt using ctrl or command + enter
@@ -19,6 +13,12 @@ app.registerExtension({
 				return;
 			}
 
+			const target = event.composedPath()[0];
+
+			if (target.tagName === "INPUT" || target.tagName === "TEXTAREA") {
+				return;
+			}
+
 			const modifierKeyIdMap = {
 				"s": "#comfy-save-button",
 				83: "#comfy-save-button",