feat: Add node to display given values

__init__.py

@@ -1,15 +1,18 @@
 from .extract_images_node   import ExtractImagesFromLatentSync
 from .extract_audio_info    import ExtractAudioInfo
 from .resize_video_frames   import ResizeVideoFrames
+from .display_any_input    import DisplayAnyInput
 
 NODE_CLASS_MAPPINGS = {
     "ExtractImagesFromLatentSync": ExtractImagesFromLatentSync,
     "ExtractAudioInfo":              ExtractAudioInfo,
-    "ResizeVideoFrames":              ResizeVideoFrames
+    "ResizeVideoFrames":              ResizeVideoFrames,
+    "DisplayAnyInput":                DisplayAnyInput
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
     "ExtractImagesFromLatentSync": "🧩 Extract Images from LatentSync",
     "ExtractAudioInfo":              "🎵 Extract Audio Info",
-    "ResizeVideoFrames":              "📐 Resize Video Frames"
+    "ResizeVideoFrames":              "📐 Resize Video Frames",
+    "DisplayAnyInput":                "🔍 Display Any Input"
 }

display_any_input.py

@@ -0,0 +1,97 @@
+import torch
+import numpy as np
+
+class DisplayAnyInput:
+    """
+    A utility node to display information about any type of input in the console.
+    This node is useful for debugging and checking the values of variables
+    at different points in a workflow.
+    """
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        """
+        Defines the inputs for the node. It accepts a single, generic input of
+        any type, and an optional title for clarity in the console.
+        """
+        return {
+            "required": {
+                "input_data": ("*", {"forceInput": True}),  # The asterisk (*) signifies any data type
+            },
+            "optional": {
+                "title": ("STRING", {"multiline": False, "default": "Display Info"}),
+            }
+        }
+
+    RETURN_TYPES = () # This node does not pass an output to the next node
+    FUNCTION = "display_info"
+    CATEGORY = "🎨 ThimPatUtils/Debugging"
+
+    def display_info(self, input_data, title):
+        """
+        The main function of the node. It prints the type, value, and other
+        relevant information about the input data to the console.
+        """
+        print(f"\n--- {title} ---")
+        
+        # Check the type of the input_data
+        if isinstance(input_data, torch.Tensor):
+            # If the input is a PyTorch tensor (e.g., IMAGE, LATENT)
+            print("Type: torch.Tensor (ComfyUI IMAGE/LATENT)")
+            print(f"Shape: {input_data.shape}")
+            print(f"Data type: {input_data.dtype}")
+            print(f"Min value: {input_data.min().item():.4f}")
+            print(f"Max value: {input_data.max().item():.4f}")
+            if input_data.nelement() <= 20: # Display small tensors fully
+                print(f"Value: \n{input_data}")
+        
+        elif isinstance(input_data, list) and all(isinstance(item, torch.Tensor) for item in input_data):
+            # If the input is a list of tensors (e.g., a list of images)
+            print("Type: List of torch.Tensor")
+            print(f"Number of tensors in list: {len(input_data)}")
+            if len(input_data) > 0:
+                first_tensor = input_data[0]
+                print(f"First tensor shape: {first_tensor.shape}")
+                print(f"First tensor data type: {first_tensor.dtype}")
+                print(f"First tensor min value: {first_tensor.min().item():.4f}")
+                print(f"First tensor max value: {first_tensor.max().item():.4f}")
+
+        elif isinstance(input_data, str):
+            # If the input is a string
+            print("Type: STRING")
+            print(f"Value: \"{input_data}\"")
+        
+        elif isinstance(input_data, (int, float)):
+            # If the input is a number
+            print("Type: NUMBER")
+            print(f"Value: {input_data}")
+
+        elif isinstance(input_data, dict):
+            # If the input is a dictionary (e.g., AUDIO)
+            print("Type: DICT")
+            print(f"Keys: {list(input_data.keys())}")
+            # Optional: print some key-value pairs for common dictionary types
+            if "duration" in input_data:
+                print(f"Duration: {input_data.get('duration')}")
+            if "sample_rate" in input_data:
+                print(f"Sample Rate: {input_data.get('sample_rate')}")
+            
+        else:
+            # For any other unsupported or unknown type
+            print("Type: UNKNOWN or unsupported")
+            print(f"Python Type: {type(input_data)}")
+            print(f"Value: {input_data}")
+
+        print("--------------------")
+        
+        return ()
+
+# A dictionary that provides the class name and display name for ComfyUI
+NODE_CLASS_MAPPINGS = {
+    "DisplayAnyInput": DisplayAnyInput
+}
+
+# A dictionary that specifies the nodes' human-readable names
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "DisplayAnyInput": "🔍 Display Any Input"
+}