From 4140263be5f7625dc6fb32c9a035eec24de769a8 Mon Sep 17 00:00:00 2001
From: Bahadir Ciloglu <bahadirciloglu@gmail.com>
Date: Sat, 1 Nov 2025 14:44:15 +0300
Subject: [PATCH] Upload local ComfyUI-master files to create_image branch

---
 .../custom_nodes/example_node.py.example      | 130 ++++++++++++++
 .../custom_nodes/websocket_image_save.py      |  44 +++++
 ComfyUI-master/input/example.png              | Bin 0 -> 8589 bytes
 .../put_audio_encoder_models_here             |   0
 .../models/checkpoints/put_checkpoints_here   |   0
 .../clip/put_clip_or_text_encoder_models_here |   0
 .../clip_vision/put_clip_vision_models_here   |   0
 .../models/configs/anything_v3.yaml           |  73 ++++++++
 .../models/configs/v1-inference.yaml          |  70 ++++++++
 .../configs/v1-inference_clip_skip_2.yaml     |  73 ++++++++
 .../v1-inference_clip_skip_2_fp16.yaml        |  74 ++++++++
 .../models/configs/v1-inference_fp16.yaml     |  71 ++++++++
 .../configs/v1-inpainting-inference.yaml      |  71 ++++++++
 .../models/configs/v2-inference-v.yaml        |  68 ++++++++
 .../models/configs/v2-inference-v_fp32.yaml   |  68 ++++++++
 .../models/configs/v2-inference.yaml          |  67 ++++++++
 .../models/configs/v2-inference_fp32.yaml     |  67 ++++++++
 .../configs/v2-inpainting-inference.yaml      | 158 ++++++++++++++++++
 .../controlnet/put_controlnets_and_t2i_here   |   0
 .../diffusers/put_diffusers_models_here       |   0
 .../put_diffusion_model_files_here            |   0
 ...eddings_or_textual_inversion_concepts_here |   0
 .../models/gligen/put_gligen_models_here      |   0
 .../hypernetworks/put_hypernetworks_here      |   0
 ComfyUI-master/models/loras/put_loras_here    |   0
 .../model_patches/put_model_patches_here      |   0
 .../photomaker/put_photomaker_models_here     |   0
 .../style_models/put_t2i_style_model_here     |   0
 .../text_encoders/put_text_encoder_files_here |   0
 .../models/unet/put_unet_files_here           |   0
 .../put_esrgan_and_other_upscale_models_here  |   0
 ComfyUI-master/models/vae/put_vae_here        |   0
 ...esd_encoder_pth_and_taesd_decoder_pth_here |   0
 .../output/_output_images_will_be_put_here    |   0
 34 files changed, 1034 insertions(+)
 create mode 100644 ComfyUI-master/custom_nodes/example_node.py.example
 create mode 100644 ComfyUI-master/custom_nodes/websocket_image_save.py
 create mode 100644 ComfyUI-master/input/example.png
 create mode 100644 ComfyUI-master/models/audio_encoders/put_audio_encoder_models_here
 create mode 100644 ComfyUI-master/models/checkpoints/put_checkpoints_here
 create mode 100644 ComfyUI-master/models/clip/put_clip_or_text_encoder_models_here
 create mode 100644 ComfyUI-master/models/clip_vision/put_clip_vision_models_here
 create mode 100644 ComfyUI-master/models/configs/anything_v3.yaml
 create mode 100644 ComfyUI-master/models/configs/v1-inference.yaml
 create mode 100644 ComfyUI-master/models/configs/v1-inference_clip_skip_2.yaml
 create mode 100644 ComfyUI-master/models/configs/v1-inference_clip_skip_2_fp16.yaml
 create mode 100644 ComfyUI-master/models/configs/v1-inference_fp16.yaml
 create mode 100644 ComfyUI-master/models/configs/v1-inpainting-inference.yaml
 create mode 100644 ComfyUI-master/models/configs/v2-inference-v.yaml
 create mode 100644 ComfyUI-master/models/configs/v2-inference-v_fp32.yaml
 create mode 100644 ComfyUI-master/models/configs/v2-inference.yaml
 create mode 100644 ComfyUI-master/models/configs/v2-inference_fp32.yaml
 create mode 100644 ComfyUI-master/models/configs/v2-inpainting-inference.yaml
 create mode 100644 ComfyUI-master/models/controlnet/put_controlnets_and_t2i_here
 create mode 100644 ComfyUI-master/models/diffusers/put_diffusers_models_here
 create mode 100644 ComfyUI-master/models/diffusion_models/put_diffusion_model_files_here
 create mode 100644 ComfyUI-master/models/embeddings/put_embeddings_or_textual_inversion_concepts_here
 create mode 100644 ComfyUI-master/models/gligen/put_gligen_models_here
 create mode 100644 ComfyUI-master/models/hypernetworks/put_hypernetworks_here
 create mode 100644 ComfyUI-master/models/loras/put_loras_here
 create mode 100644 ComfyUI-master/models/model_patches/put_model_patches_here
 create mode 100644 ComfyUI-master/models/photomaker/put_photomaker_models_here
 create mode 100644 ComfyUI-master/models/style_models/put_t2i_style_model_here
 create mode 100644 ComfyUI-master/models/text_encoders/put_text_encoder_files_here
 create mode 100644 ComfyUI-master/models/unet/put_unet_files_here
 create mode 100644 ComfyUI-master/models/upscale_models/put_esrgan_and_other_upscale_models_here
 create mode 100644 ComfyUI-master/models/vae/put_vae_here
 create mode 100644 ComfyUI-master/models/vae_approx/put_taesd_encoder_pth_and_taesd_decoder_pth_here
 create mode 100644 ComfyUI-master/output/_output_images_will_be_put_here

diff --git a/ComfyUI-master/custom_nodes/example_node.py.example b/ComfyUI-master/custom_nodes/example_node.py.example
new file mode 100644
index 000000000..779c35787
--- /dev/null
+++ b/ComfyUI-master/custom_nodes/example_node.py.example
@@ -0,0 +1,130 @@
+from typing_extensions import override
+
+from comfy_api.latest import ComfyExtension, io
+
+
+class Example(io.ComfyNode):
+    """
+    An example node
+
+    Class methods
+    -------------
+    define_schema (io.Schema):
+        Tell the main program the metadata, input, output parameters of nodes.
+    fingerprint_inputs:
+        optional method to control when the node is re executed.
+    check_lazy_status:
+        optional method to control list of input names that need to be evaluated.
+
+    """
+
+    @classmethod
+    def define_schema(cls) -> io.Schema:
+        """
+            Return a schema which contains all information about the node.
+            Some types: "Model", "Vae", "Clip", "Conditioning", "Latent", "Image", "Int", "String", "Float", "Combo".
+            For outputs the "io.Model.Output" should be used, for inputs the "io.Model.Input" can be used.
+            The type can be a "Combo" - this will be a list for selection.
+        """
+        return io.Schema(
+            node_id="Example",
+            display_name="Example Node",
+            category="Example",
+            inputs=[
+                io.Image.Input("image"),
+                io.Int.Input(
+                    "int_field",
+                    min=0,
+                    max=4096,
+                    step=64, # Slider's step
+                    display_mode=io.NumberDisplay.number,  # Cosmetic only: display as "number" or "slider"
+                    lazy=True,  # Will only be evaluated if check_lazy_status requires it
+                ),
+                io.Float.Input(
+                    "float_field",
+                    default=1.0,
+                    min=0.0,
+                    max=10.0,
+                    step=0.01,
+                    round=0.001, #The value representing the precision to round to, will be set to the step value by default. Can be set to False to disable rounding.
+                    display_mode=io.NumberDisplay.number,
+                    lazy=True,
+                ),
+                io.Combo.Input("print_to_screen", options=["enable", "disable"]),
+                io.String.Input(
+                    "string_field",
+                    multiline=False,  # True if you want the field to look like the one on the ClipTextEncode node
+                    default="Hello world!",
+                    lazy=True,
+                )
+            ],
+            outputs=[
+                io.Image.Output(),
+            ],
+        )
+
+    @classmethod
+    def check_lazy_status(cls, image, string_field, int_field, float_field, print_to_screen):
+        """
+            Return a list of input names that need to be evaluated.
+
+            This function will be called if there are any lazy inputs which have not yet been
+            evaluated. As long as you return at least one field which has not yet been evaluated
+            (and more exist), this function will be called again once the value of the requested
+            field is available.
+
+            Any evaluated inputs will be passed as arguments to this function. Any unevaluated
+            inputs will have the value None.
+        """
+        if print_to_screen == "enable":
+            return ["int_field", "float_field", "string_field"]
+        else:
+            return []
+
+    @classmethod
+    def execute(cls, image, string_field, int_field, float_field, print_to_screen) -> io.NodeOutput:
+        if print_to_screen == "enable":
+            print(f"""Your input contains:
+                string_field aka input text: {string_field}
+                int_field: {int_field}
+                float_field: {float_field}
+            """)
+        #do some processing on the image, in this example I just invert it
+        image = 1.0 - image
+        return io.NodeOutput(image)
+
+    """
+        The node will always be re executed if any of the inputs change but
+        this method can be used to force the node to execute again even when the inputs don't change.
+        You can make this node return a number or a string. This value will be compared to the one returned the last time the node was
+        executed, if it is different the node will be executed again.
+        This method is used in the core repo for the LoadImage node where they return the image hash as a string, if the image hash
+        changes between executions the LoadImage node is executed again.
+    """
+    #@classmethod
+    #def fingerprint_inputs(s, image, string_field, int_field, float_field, print_to_screen):
+    #    return ""
+
+# Set the web directory, any .js file in that directory will be loaded by the frontend as a frontend extension
+# WEB_DIRECTORY = "./somejs"
+
+
+# Add custom API routes, using router
+from aiohttp import web
+from server import PromptServer
+
+@PromptServer.instance.routes.get("/hello")
+async def get_hello(request):
+    return web.json_response("hello")
+
+
+class ExampleExtension(ComfyExtension):
+    @override
+    async def get_node_list(self) -> list[type[io.ComfyNode]]:
+        return [
+            Example,
+        ]
+
+
+async def comfy_entrypoint() -> ExampleExtension:  # ComfyUI calls this to load your extension and its nodes.
+    return ExampleExtension()
diff --git a/ComfyUI-master/custom_nodes/websocket_image_save.py b/ComfyUI-master/custom_nodes/websocket_image_save.py
new file mode 100644
index 000000000..15f87f9f5
--- /dev/null
+++ b/ComfyUI-master/custom_nodes/websocket_image_save.py
@@ -0,0 +1,44 @@
+from PIL import Image
+import numpy as np
+import comfy.utils
+import time
+
+#You can use this node to save full size images through the websocket, the
+#images will be sent in exactly the same format as the image previews: as
+#binary images on the websocket with a 8 byte header indicating the type
+#of binary message (first 4 bytes) and the image format (next 4 bytes).
+
+#Note that no metadata will be put in the images saved with this node.
+
+class SaveImageWebsocket:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required":
+                    {"images": ("IMAGE", ),}
+                }
+
+    RETURN_TYPES = ()
+    FUNCTION = "save_images"
+
+    OUTPUT_NODE = True
+
+    CATEGORY = "api/image"
+
+    def save_images(self, images):
+        pbar = comfy.utils.ProgressBar(images.shape[0])
+        step = 0
+        for image in images:
+            i = 255. * image.cpu().numpy()
+            img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
+            pbar.update_absolute(step, images.shape[0], ("PNG", img, None))
+            step += 1
+
+        return {}
+
+    @classmethod
+    def IS_CHANGED(s, images):
+        return time.time()
+
+NODE_CLASS_MAPPINGS = {
+    "SaveImageWebsocket": SaveImageWebsocket,
+}
diff --git a/ComfyUI-master/input/example.png b/ComfyUI-master/input/example.png
new file mode 100644
index 0000000000000000000000000000000000000000..7b7f3c9cbbe6d8750c4a9eaf65d6ae4d2f108f79
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diff --git a/ComfyUI-master/models/audio_encoders/put_audio_encoder_models_here b/ComfyUI-master/models/audio_encoders/put_audio_encoder_models_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/checkpoints/put_checkpoints_here b/ComfyUI-master/models/checkpoints/put_checkpoints_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/clip/put_clip_or_text_encoder_models_here b/ComfyUI-master/models/clip/put_clip_or_text_encoder_models_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/clip_vision/put_clip_vision_models_here b/ComfyUI-master/models/clip_vision/put_clip_vision_models_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/configs/anything_v3.yaml b/ComfyUI-master/models/configs/anything_v3.yaml
new file mode 100644
index 000000000..8bcfe584a
--- /dev/null
+++ b/ComfyUI-master/models/configs/anything_v3.yaml
@@ -0,0 +1,73 @@
+model:
+  base_learning_rate: 1.0e-04
+  target: ldm.models.diffusion.ddpm.LatentDiffusion
+  params:
+    linear_start: 0.00085
+    linear_end: 0.0120
+    num_timesteps_cond: 1
+    log_every_t: 200
+    timesteps: 1000
+    first_stage_key: "jpg"
+    cond_stage_key: "txt"
+    image_size: 64
+    channels: 4
+    cond_stage_trainable: false   # Note: different from the one we trained before
+    conditioning_key: crossattn
+    monitor: val/loss_simple_ema
+    scale_factor: 0.18215
+    use_ema: False
+
+    scheduler_config: # 10000 warmup steps
+      target: ldm.lr_scheduler.LambdaLinearScheduler
+      params:
+        warm_up_steps: [ 10000 ]
+        cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
+        f_start: [ 1.e-6 ]
+        f_max: [ 1. ]
+        f_min: [ 1. ]
+
+    unet_config:
+      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        image_size: 32 # unused
+        in_channels: 4
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [ 4, 2, 1 ]
+        num_res_blocks: 2
+        channel_mult: [ 1, 2, 4, 4 ]
+        num_heads: 8
+        use_spatial_transformer: True
+        transformer_depth: 1
+        context_dim: 768
+        use_checkpoint: True
+        legacy: False
+
+    first_stage_config:
+      target: ldm.models.autoencoder.AutoencoderKL
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          double_z: true
+          z_channels: 4
+          resolution: 256
+          in_channels: 3
+          out_ch: 3
+          ch: 128
+          ch_mult:
+          - 1
+          - 2
+          - 4
+          - 4
+          num_res_blocks: 2
+          attn_resolutions: []
+          dropout: 0.0
+        lossconfig:
+          target: torch.nn.Identity
+
+    cond_stage_config:
+      target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
+      params:
+        layer: "hidden"
+        layer_idx: -2
diff --git a/ComfyUI-master/models/configs/v1-inference.yaml b/ComfyUI-master/models/configs/v1-inference.yaml
new file mode 100644
index 000000000..d4effe569
--- /dev/null
+++ b/ComfyUI-master/models/configs/v1-inference.yaml
@@ -0,0 +1,70 @@
+model:
+  base_learning_rate: 1.0e-04
+  target: ldm.models.diffusion.ddpm.LatentDiffusion
+  params:
+    linear_start: 0.00085
+    linear_end: 0.0120
+    num_timesteps_cond: 1
+    log_every_t: 200
+    timesteps: 1000
+    first_stage_key: "jpg"
+    cond_stage_key: "txt"
+    image_size: 64
+    channels: 4
+    cond_stage_trainable: false   # Note: different from the one we trained before
+    conditioning_key: crossattn
+    monitor: val/loss_simple_ema
+    scale_factor: 0.18215
+    use_ema: False
+
+    scheduler_config: # 10000 warmup steps
+      target: ldm.lr_scheduler.LambdaLinearScheduler
+      params:
+        warm_up_steps: [ 10000 ]
+        cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
+        f_start: [ 1.e-6 ]
+        f_max: [ 1. ]
+        f_min: [ 1. ]
+
+    unet_config:
+      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        image_size: 32 # unused
+        in_channels: 4
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [ 4, 2, 1 ]
+        num_res_blocks: 2
+        channel_mult: [ 1, 2, 4, 4 ]
+        num_heads: 8
+        use_spatial_transformer: True
+        transformer_depth: 1
+        context_dim: 768
+        use_checkpoint: True
+        legacy: False
+
+    first_stage_config:
+      target: ldm.models.autoencoder.AutoencoderKL
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          double_z: true
+          z_channels: 4
+          resolution: 256
+          in_channels: 3
+          out_ch: 3
+          ch: 128
+          ch_mult:
+          - 1
+          - 2
+          - 4
+          - 4
+          num_res_blocks: 2
+          attn_resolutions: []
+          dropout: 0.0
+        lossconfig:
+          target: torch.nn.Identity
+
+    cond_stage_config:
+      target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
diff --git a/ComfyUI-master/models/configs/v1-inference_clip_skip_2.yaml b/ComfyUI-master/models/configs/v1-inference_clip_skip_2.yaml
new file mode 100644
index 000000000..8bcfe584a
--- /dev/null
+++ b/ComfyUI-master/models/configs/v1-inference_clip_skip_2.yaml
@@ -0,0 +1,73 @@
+model:
+  base_learning_rate: 1.0e-04
+  target: ldm.models.diffusion.ddpm.LatentDiffusion
+  params:
+    linear_start: 0.00085
+    linear_end: 0.0120
+    num_timesteps_cond: 1
+    log_every_t: 200
+    timesteps: 1000
+    first_stage_key: "jpg"
+    cond_stage_key: "txt"
+    image_size: 64
+    channels: 4
+    cond_stage_trainable: false   # Note: different from the one we trained before
+    conditioning_key: crossattn
+    monitor: val/loss_simple_ema
+    scale_factor: 0.18215
+    use_ema: False
+
+    scheduler_config: # 10000 warmup steps
+      target: ldm.lr_scheduler.LambdaLinearScheduler
+      params:
+        warm_up_steps: [ 10000 ]
+        cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
+        f_start: [ 1.e-6 ]
+        f_max: [ 1. ]
+        f_min: [ 1. ]
+
+    unet_config:
+      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        image_size: 32 # unused
+        in_channels: 4
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [ 4, 2, 1 ]
+        num_res_blocks: 2
+        channel_mult: [ 1, 2, 4, 4 ]
+        num_heads: 8
+        use_spatial_transformer: True
+        transformer_depth: 1
+        context_dim: 768
+        use_checkpoint: True
+        legacy: False
+
+    first_stage_config:
+      target: ldm.models.autoencoder.AutoencoderKL
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          double_z: true
+          z_channels: 4
+          resolution: 256
+          in_channels: 3
+          out_ch: 3
+          ch: 128
+          ch_mult:
+          - 1
+          - 2
+          - 4
+          - 4
+          num_res_blocks: 2
+          attn_resolutions: []
+          dropout: 0.0
+        lossconfig:
+          target: torch.nn.Identity
+
+    cond_stage_config:
+      target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
+      params:
+        layer: "hidden"
+        layer_idx: -2
diff --git a/ComfyUI-master/models/configs/v1-inference_clip_skip_2_fp16.yaml b/ComfyUI-master/models/configs/v1-inference_clip_skip_2_fp16.yaml
new file mode 100644
index 000000000..7eca31c7b
--- /dev/null
+++ b/ComfyUI-master/models/configs/v1-inference_clip_skip_2_fp16.yaml
@@ -0,0 +1,74 @@
+model:
+  base_learning_rate: 1.0e-04
+  target: ldm.models.diffusion.ddpm.LatentDiffusion
+  params:
+    linear_start: 0.00085
+    linear_end: 0.0120
+    num_timesteps_cond: 1
+    log_every_t: 200
+    timesteps: 1000
+    first_stage_key: "jpg"
+    cond_stage_key: "txt"
+    image_size: 64
+    channels: 4
+    cond_stage_trainable: false   # Note: different from the one we trained before
+    conditioning_key: crossattn
+    monitor: val/loss_simple_ema
+    scale_factor: 0.18215
+    use_ema: False
+
+    scheduler_config: # 10000 warmup steps
+      target: ldm.lr_scheduler.LambdaLinearScheduler
+      params:
+        warm_up_steps: [ 10000 ]
+        cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
+        f_start: [ 1.e-6 ]
+        f_max: [ 1. ]
+        f_min: [ 1. ]
+
+    unet_config:
+      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        use_fp16: True
+        image_size: 32 # unused
+        in_channels: 4
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [ 4, 2, 1 ]
+        num_res_blocks: 2
+        channel_mult: [ 1, 2, 4, 4 ]
+        num_heads: 8
+        use_spatial_transformer: True
+        transformer_depth: 1
+        context_dim: 768
+        use_checkpoint: True
+        legacy: False
+
+    first_stage_config:
+      target: ldm.models.autoencoder.AutoencoderKL
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          double_z: true
+          z_channels: 4
+          resolution: 256
+          in_channels: 3
+          out_ch: 3
+          ch: 128
+          ch_mult:
+          - 1
+          - 2
+          - 4
+          - 4
+          num_res_blocks: 2
+          attn_resolutions: []
+          dropout: 0.0
+        lossconfig:
+          target: torch.nn.Identity
+
+    cond_stage_config:
+      target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
+      params:
+        layer: "hidden"
+        layer_idx: -2
diff --git a/ComfyUI-master/models/configs/v1-inference_fp16.yaml b/ComfyUI-master/models/configs/v1-inference_fp16.yaml
new file mode 100644
index 000000000..147f42b17
--- /dev/null
+++ b/ComfyUI-master/models/configs/v1-inference_fp16.yaml
@@ -0,0 +1,71 @@
+model:
+  base_learning_rate: 1.0e-04
+  target: ldm.models.diffusion.ddpm.LatentDiffusion
+  params:
+    linear_start: 0.00085
+    linear_end: 0.0120
+    num_timesteps_cond: 1
+    log_every_t: 200
+    timesteps: 1000
+    first_stage_key: "jpg"
+    cond_stage_key: "txt"
+    image_size: 64
+    channels: 4
+    cond_stage_trainable: false   # Note: different from the one we trained before
+    conditioning_key: crossattn
+    monitor: val/loss_simple_ema
+    scale_factor: 0.18215
+    use_ema: False
+
+    scheduler_config: # 10000 warmup steps
+      target: ldm.lr_scheduler.LambdaLinearScheduler
+      params:
+        warm_up_steps: [ 10000 ]
+        cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
+        f_start: [ 1.e-6 ]
+        f_max: [ 1. ]
+        f_min: [ 1. ]
+
+    unet_config:
+      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        use_fp16: True
+        image_size: 32 # unused
+        in_channels: 4
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [ 4, 2, 1 ]
+        num_res_blocks: 2
+        channel_mult: [ 1, 2, 4, 4 ]
+        num_heads: 8
+        use_spatial_transformer: True
+        transformer_depth: 1
+        context_dim: 768
+        use_checkpoint: True
+        legacy: False
+
+    first_stage_config:
+      target: ldm.models.autoencoder.AutoencoderKL
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          double_z: true
+          z_channels: 4
+          resolution: 256
+          in_channels: 3
+          out_ch: 3
+          ch: 128
+          ch_mult:
+          - 1
+          - 2
+          - 4
+          - 4
+          num_res_blocks: 2
+          attn_resolutions: []
+          dropout: 0.0
+        lossconfig:
+          target: torch.nn.Identity
+
+    cond_stage_config:
+      target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
diff --git a/ComfyUI-master/models/configs/v1-inpainting-inference.yaml b/ComfyUI-master/models/configs/v1-inpainting-inference.yaml
new file mode 100644
index 000000000..45f3f82d4
--- /dev/null
+++ b/ComfyUI-master/models/configs/v1-inpainting-inference.yaml
@@ -0,0 +1,71 @@
+model:
+  base_learning_rate: 7.5e-05
+  target: ldm.models.diffusion.ddpm.LatentInpaintDiffusion
+  params:
+    linear_start: 0.00085
+    linear_end: 0.0120
+    num_timesteps_cond: 1
+    log_every_t: 200
+    timesteps: 1000
+    first_stage_key: "jpg"
+    cond_stage_key: "txt"
+    image_size: 64
+    channels: 4
+    cond_stage_trainable: false   # Note: different from the one we trained before
+    conditioning_key: hybrid   # important
+    monitor: val/loss_simple_ema
+    scale_factor: 0.18215
+    finetune_keys: null
+
+    scheduler_config: # 10000 warmup steps
+      target: ldm.lr_scheduler.LambdaLinearScheduler
+      params:
+        warm_up_steps: [ 2500 ] # NOTE for resuming. use 10000 if starting from scratch
+        cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
+        f_start: [ 1.e-6 ]
+        f_max: [ 1. ]
+        f_min: [ 1. ]
+
+    unet_config:
+      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        image_size: 32 # unused
+        in_channels: 9  # 4 data + 4 downscaled image + 1 mask
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [ 4, 2, 1 ]
+        num_res_blocks: 2
+        channel_mult: [ 1, 2, 4, 4 ]
+        num_heads: 8
+        use_spatial_transformer: True
+        transformer_depth: 1
+        context_dim: 768
+        use_checkpoint: True
+        legacy: False
+
+    first_stage_config:
+      target: ldm.models.autoencoder.AutoencoderKL
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          double_z: true
+          z_channels: 4
+          resolution: 256
+          in_channels: 3
+          out_ch: 3
+          ch: 128
+          ch_mult:
+          - 1
+          - 2
+          - 4
+          - 4
+          num_res_blocks: 2
+          attn_resolutions: []
+          dropout: 0.0
+        lossconfig:
+          target: torch.nn.Identity
+
+    cond_stage_config:
+      target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
+
diff --git a/ComfyUI-master/models/configs/v2-inference-v.yaml b/ComfyUI-master/models/configs/v2-inference-v.yaml
new file mode 100644
index 000000000..8ec8dfbfe
--- /dev/null
+++ b/ComfyUI-master/models/configs/v2-inference-v.yaml
@@ -0,0 +1,68 @@
+model:
+  base_learning_rate: 1.0e-4
+  target: ldm.models.diffusion.ddpm.LatentDiffusion
+  params:
+    parameterization: "v"
+    linear_start: 0.00085
+    linear_end: 0.0120
+    num_timesteps_cond: 1
+    log_every_t: 200
+    timesteps: 1000
+    first_stage_key: "jpg"
+    cond_stage_key: "txt"
+    image_size: 64
+    channels: 4
+    cond_stage_trainable: false
+    conditioning_key: crossattn
+    monitor: val/loss_simple_ema
+    scale_factor: 0.18215
+    use_ema: False # we set this to false because this is an inference only config
+
+    unet_config:
+      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        use_checkpoint: True
+        use_fp16: True
+        image_size: 32 # unused
+        in_channels: 4
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [ 4, 2, 1 ]
+        num_res_blocks: 2
+        channel_mult: [ 1, 2, 4, 4 ]
+        num_head_channels: 64 # need to fix for flash-attn
+        use_spatial_transformer: True
+        use_linear_in_transformer: True
+        transformer_depth: 1
+        context_dim: 1024
+        legacy: False
+
+    first_stage_config:
+      target: ldm.models.autoencoder.AutoencoderKL
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          #attn_type: "vanilla-xformers"
+          double_z: true
+          z_channels: 4
+          resolution: 256
+          in_channels: 3
+          out_ch: 3
+          ch: 128
+          ch_mult:
+          - 1
+          - 2
+          - 4
+          - 4
+          num_res_blocks: 2
+          attn_resolutions: []
+          dropout: 0.0
+        lossconfig:
+          target: torch.nn.Identity
+
+    cond_stage_config:
+      target: ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder
+      params:
+        freeze: True
+        layer: "penultimate"
diff --git a/ComfyUI-master/models/configs/v2-inference-v_fp32.yaml b/ComfyUI-master/models/configs/v2-inference-v_fp32.yaml
new file mode 100644
index 000000000..d5c9b9cb2
--- /dev/null
+++ b/ComfyUI-master/models/configs/v2-inference-v_fp32.yaml
@@ -0,0 +1,68 @@
+model:
+  base_learning_rate: 1.0e-4
+  target: ldm.models.diffusion.ddpm.LatentDiffusion
+  params:
+    parameterization: "v"
+    linear_start: 0.00085
+    linear_end: 0.0120
+    num_timesteps_cond: 1
+    log_every_t: 200
+    timesteps: 1000
+    first_stage_key: "jpg"
+    cond_stage_key: "txt"
+    image_size: 64
+    channels: 4
+    cond_stage_trainable: false
+    conditioning_key: crossattn
+    monitor: val/loss_simple_ema
+    scale_factor: 0.18215
+    use_ema: False # we set this to false because this is an inference only config
+
+    unet_config:
+      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        use_checkpoint: True
+        use_fp16: False
+        image_size: 32 # unused
+        in_channels: 4
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [ 4, 2, 1 ]
+        num_res_blocks: 2
+        channel_mult: [ 1, 2, 4, 4 ]
+        num_head_channels: 64 # need to fix for flash-attn
+        use_spatial_transformer: True
+        use_linear_in_transformer: True
+        transformer_depth: 1
+        context_dim: 1024
+        legacy: False
+
+    first_stage_config:
+      target: ldm.models.autoencoder.AutoencoderKL
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          #attn_type: "vanilla-xformers"
+          double_z: true
+          z_channels: 4
+          resolution: 256
+          in_channels: 3
+          out_ch: 3
+          ch: 128
+          ch_mult:
+          - 1
+          - 2
+          - 4
+          - 4
+          num_res_blocks: 2
+          attn_resolutions: []
+          dropout: 0.0
+        lossconfig:
+          target: torch.nn.Identity
+
+    cond_stage_config:
+      target: ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder
+      params:
+        freeze: True
+        layer: "penultimate"
diff --git a/ComfyUI-master/models/configs/v2-inference.yaml b/ComfyUI-master/models/configs/v2-inference.yaml
new file mode 100644
index 000000000..152c4f3c2
--- /dev/null
+++ b/ComfyUI-master/models/configs/v2-inference.yaml
@@ -0,0 +1,67 @@
+model:
+  base_learning_rate: 1.0e-4
+  target: ldm.models.diffusion.ddpm.LatentDiffusion
+  params:
+    linear_start: 0.00085
+    linear_end: 0.0120
+    num_timesteps_cond: 1
+    log_every_t: 200
+    timesteps: 1000
+    first_stage_key: "jpg"
+    cond_stage_key: "txt"
+    image_size: 64
+    channels: 4
+    cond_stage_trainable: false
+    conditioning_key: crossattn
+    monitor: val/loss_simple_ema
+    scale_factor: 0.18215
+    use_ema: False # we set this to false because this is an inference only config
+
+    unet_config:
+      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        use_checkpoint: True
+        use_fp16: True
+        image_size: 32 # unused
+        in_channels: 4
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [ 4, 2, 1 ]
+        num_res_blocks: 2
+        channel_mult: [ 1, 2, 4, 4 ]
+        num_head_channels: 64 # need to fix for flash-attn
+        use_spatial_transformer: True
+        use_linear_in_transformer: True
+        transformer_depth: 1
+        context_dim: 1024
+        legacy: False
+
+    first_stage_config:
+      target: ldm.models.autoencoder.AutoencoderKL
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          #attn_type: "vanilla-xformers"
+          double_z: true
+          z_channels: 4
+          resolution: 256
+          in_channels: 3
+          out_ch: 3
+          ch: 128
+          ch_mult:
+          - 1
+          - 2
+          - 4
+          - 4
+          num_res_blocks: 2
+          attn_resolutions: []
+          dropout: 0.0
+        lossconfig:
+          target: torch.nn.Identity
+
+    cond_stage_config:
+      target: ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder
+      params:
+        freeze: True
+        layer: "penultimate"
diff --git a/ComfyUI-master/models/configs/v2-inference_fp32.yaml b/ComfyUI-master/models/configs/v2-inference_fp32.yaml
new file mode 100644
index 000000000..0d03231f3
--- /dev/null
+++ b/ComfyUI-master/models/configs/v2-inference_fp32.yaml
@@ -0,0 +1,67 @@
+model:
+  base_learning_rate: 1.0e-4
+  target: ldm.models.diffusion.ddpm.LatentDiffusion
+  params:
+    linear_start: 0.00085
+    linear_end: 0.0120
+    num_timesteps_cond: 1
+    log_every_t: 200
+    timesteps: 1000
+    first_stage_key: "jpg"
+    cond_stage_key: "txt"
+    image_size: 64
+    channels: 4
+    cond_stage_trainable: false
+    conditioning_key: crossattn
+    monitor: val/loss_simple_ema
+    scale_factor: 0.18215
+    use_ema: False # we set this to false because this is an inference only config
+
+    unet_config:
+      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        use_checkpoint: True
+        use_fp16: False
+        image_size: 32 # unused
+        in_channels: 4
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [ 4, 2, 1 ]
+        num_res_blocks: 2
+        channel_mult: [ 1, 2, 4, 4 ]
+        num_head_channels: 64 # need to fix for flash-attn
+        use_spatial_transformer: True
+        use_linear_in_transformer: True
+        transformer_depth: 1
+        context_dim: 1024
+        legacy: False
+
+    first_stage_config:
+      target: ldm.models.autoencoder.AutoencoderKL
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          #attn_type: "vanilla-xformers"
+          double_z: true
+          z_channels: 4
+          resolution: 256
+          in_channels: 3
+          out_ch: 3
+          ch: 128
+          ch_mult:
+          - 1
+          - 2
+          - 4
+          - 4
+          num_res_blocks: 2
+          attn_resolutions: []
+          dropout: 0.0
+        lossconfig:
+          target: torch.nn.Identity
+
+    cond_stage_config:
+      target: ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder
+      params:
+        freeze: True
+        layer: "penultimate"
diff --git a/ComfyUI-master/models/configs/v2-inpainting-inference.yaml b/ComfyUI-master/models/configs/v2-inpainting-inference.yaml
new file mode 100644
index 000000000..32a9471d7
--- /dev/null
+++ b/ComfyUI-master/models/configs/v2-inpainting-inference.yaml
@@ -0,0 +1,158 @@
+model:
+  base_learning_rate: 5.0e-05
+  target: ldm.models.diffusion.ddpm.LatentInpaintDiffusion
+  params:
+    linear_start: 0.00085
+    linear_end: 0.0120
+    num_timesteps_cond: 1
+    log_every_t: 200
+    timesteps: 1000
+    first_stage_key: "jpg"
+    cond_stage_key: "txt"
+    image_size: 64
+    channels: 4
+    cond_stage_trainable: false
+    conditioning_key: hybrid
+    scale_factor: 0.18215
+    monitor: val/loss_simple_ema
+    finetune_keys: null
+    use_ema: False
+
+    unet_config:
+      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        use_checkpoint: True
+        image_size: 32 # unused
+        in_channels: 9
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [ 4, 2, 1 ]
+        num_res_blocks: 2
+        channel_mult: [ 1, 2, 4, 4 ]
+        num_head_channels: 64 # need to fix for flash-attn
+        use_spatial_transformer: True
+        use_linear_in_transformer: True
+        transformer_depth: 1
+        context_dim: 1024
+        legacy: False
+
+    first_stage_config:
+      target: ldm.models.autoencoder.AutoencoderKL
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          #attn_type: "vanilla-xformers"
+          double_z: true
+          z_channels: 4
+          resolution: 256
+          in_channels: 3
+          out_ch: 3
+          ch: 128
+          ch_mult:
+            - 1
+            - 2
+            - 4
+            - 4
+          num_res_blocks: 2
+          attn_resolutions: [ ]
+          dropout: 0.0
+        lossconfig:
+          target: torch.nn.Identity
+
+    cond_stage_config:
+      target: ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder
+      params:
+        freeze: True
+        layer: "penultimate"
+
+
+data:
+  target: ldm.data.laion.WebDataModuleFromConfig
+  params:
+    tar_base: null  # for concat as in LAION-A
+    p_unsafe_threshold: 0.1
+    filter_word_list: "data/filters.yaml"
+    max_pwatermark: 0.45
+    batch_size: 8
+    num_workers: 6
+    multinode: True
+    min_size: 512
+    train:
+      shards:
+        - "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-0/{00000..18699}.tar -"
+        - "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-1/{00000..18699}.tar -"
+        - "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-2/{00000..18699}.tar -"
+        - "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-3/{00000..18699}.tar -"
+        - "pipe:aws s3 cp s3://stability-aws/laion-a-native/part-4/{00000..18699}.tar -"  #{00000-94333}.tar"
+      shuffle: 10000
+      image_key: jpg
+      image_transforms:
+      - target: torchvision.transforms.Resize
+        params:
+          size: 512
+          interpolation: 3
+      - target: torchvision.transforms.RandomCrop
+        params:
+          size: 512
+      postprocess:
+        target: ldm.data.laion.AddMask
+        params:
+          mode: "512train-large"
+          p_drop: 0.25
+    # NOTE use enough shards to avoid empty validation loops in workers
+    validation:
+      shards:
+        - "pipe:aws s3 cp s3://deep-floyd-s3/datasets/laion_cleaned-part5/{93001..94333}.tar - "
+      shuffle: 0
+      image_key: jpg
+      image_transforms:
+      - target: torchvision.transforms.Resize
+        params:
+          size: 512
+          interpolation: 3
+      - target: torchvision.transforms.CenterCrop
+        params:
+          size: 512
+      postprocess:
+        target: ldm.data.laion.AddMask
+        params:
+          mode: "512train-large"
+          p_drop: 0.25
+
+lightning:
+  find_unused_parameters: True
+  modelcheckpoint:
+    params:
+      every_n_train_steps: 5000
+
+  callbacks:
+    metrics_over_trainsteps_checkpoint:
+      params:
+        every_n_train_steps: 10000
+
+    image_logger:
+      target: main.ImageLogger
+      params:
+        enable_autocast: False
+        disabled: False
+        batch_frequency: 1000
+        max_images: 4
+        increase_log_steps: False
+        log_first_step: False
+        log_images_kwargs:
+          use_ema_scope: False
+          inpaint: False
+          plot_progressive_rows: False
+          plot_diffusion_rows: False
+          N: 4
+          unconditional_guidance_scale: 5.0
+          unconditional_guidance_label: [""]
+          ddim_steps: 50  # todo check these out for depth2img,
+          ddim_eta: 0.0   # todo check these out for depth2img,
+
+  trainer:
+    benchmark: True
+    val_check_interval: 5000000
+    num_sanity_val_steps: 0
+    accumulate_grad_batches: 1
diff --git a/ComfyUI-master/models/controlnet/put_controlnets_and_t2i_here b/ComfyUI-master/models/controlnet/put_controlnets_and_t2i_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/diffusers/put_diffusers_models_here b/ComfyUI-master/models/diffusers/put_diffusers_models_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/diffusion_models/put_diffusion_model_files_here b/ComfyUI-master/models/diffusion_models/put_diffusion_model_files_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/embeddings/put_embeddings_or_textual_inversion_concepts_here b/ComfyUI-master/models/embeddings/put_embeddings_or_textual_inversion_concepts_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/gligen/put_gligen_models_here b/ComfyUI-master/models/gligen/put_gligen_models_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/hypernetworks/put_hypernetworks_here b/ComfyUI-master/models/hypernetworks/put_hypernetworks_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/loras/put_loras_here b/ComfyUI-master/models/loras/put_loras_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/model_patches/put_model_patches_here b/ComfyUI-master/models/model_patches/put_model_patches_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/photomaker/put_photomaker_models_here b/ComfyUI-master/models/photomaker/put_photomaker_models_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/style_models/put_t2i_style_model_here b/ComfyUI-master/models/style_models/put_t2i_style_model_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/text_encoders/put_text_encoder_files_here b/ComfyUI-master/models/text_encoders/put_text_encoder_files_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/unet/put_unet_files_here b/ComfyUI-master/models/unet/put_unet_files_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/upscale_models/put_esrgan_and_other_upscale_models_here b/ComfyUI-master/models/upscale_models/put_esrgan_and_other_upscale_models_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/vae/put_vae_here b/ComfyUI-master/models/vae/put_vae_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/models/vae_approx/put_taesd_encoder_pth_and_taesd_decoder_pth_here b/ComfyUI-master/models/vae_approx/put_taesd_encoder_pth_and_taesd_decoder_pth_here
new file mode 100644
index 000000000..e69de29bb
diff --git a/ComfyUI-master/output/_output_images_will_be_put_here b/ComfyUI-master/output/_output_images_will_be_put_here
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index 000000000..e69de29bb