Added code for log prints and added session image count

app.py

@@ -1,7 +1,5 @@
 #@title Prepare the Concepts Library to be used
 
-
-
 import requests
 import os
 import gradio as gr
@@ -12,6 +10,9 @@ from diffusers import StableDiffusionPipeline
 from huggingface_hub import HfApi
 from transformers import CLIPTextModel, CLIPTokenizer
 import html
+import datetime
+
+image_count = 0
 
 community_icon_html = ""
 
@@ -126,9 +127,21 @@ def image_prompt(prompt, guidance, steps, seed, height, width):
   if square_pixels > 640000:
       height = 640000 // width
   generator = torch.Generator(device="cuda").manual_seed(int(seed))
+
+  height=int((height // 8) * 8)
+  width=int((width // 8) * 8)
+
+  image_count += 1
+  curr_time = datetime.datetime.now()
+
+  print("----- advanced tab prompt ------------------------------")
+  print(f"prompt: {prompt}, size: {width}px x {height}px, guidance: {guidance}, steps: {steps}, seed: {int(seed)}")
+  print(f"image_count: {image_count}, datetime: `{e}`")
+  print("-------------------------------------------------------")
+    
   return (
-      pipe(prompt=prompt, guidance_scale=guidance, num_inference_steps=steps, generator=generator, height=int((height // 8) * 8), width=int((width // 8) * 8)).images[0], 
-      f"prompt = '{prompt}'\nseed = {int(seed)}\nguidance_scale = {guidance}\ninference steps = {steps}\nheight = {int((height // 8) * 8)}\nwidth = {int((width // 8) * 8)}"
+      pipe(prompt=prompt, guidance_scale=guidance, num_inference_steps=steps, generator=generator, height=height, width=width).images[0], 
+      f"prompt: '{prompt}', seed = {int(seed)},\nheight: {height}px, width: {width}px,\nguidance: {guidance}, steps: {steps}"
       )
 
 
@@ -259,11 +272,23 @@ def simple_image_prompt(prompt, dropdown, size_dropdown):
       
   steps = 30
 
+  height=int((height // 8) * 8)
+  width=int((width // 8) * 8)
+
   prompt = prompt + DROPDOWNS[dropdown]
   generator = torch.Generator(device="cuda").manual_seed(int(seed))
+
+  image_count += 1
+  curr_time = datetime.datetime.now()
+    
+  print("----- welcome / beta tab prompt ------------------------------")
+  print(f"prompt: {prompt}, size: {width}px x {height}px, guidance: {guidance}, steps: {steps}, seed: {int(seed)}")
+  print(f"image_count: {image_count}, datetime: `{e}`")
+  print("-------------------------------------------------------")
+    
   return (
-      pipe(prompt=prompt, guidance_scale=guidance, num_inference_steps=steps, generator=generator, height=int((height // 8) * 8), width=int((width // 8) * 8)).images[0], 
-      f"prompt = '{prompt}'\nseed = {int(seed)}\nguidance_scale = {guidance}\ninference steps = {steps}\nheight = {int((height // 8) * 8)}\nwidth = {int((width // 8) * 8)}"
+      pipe(prompt=prompt, guidance_scale=guidance, num_inference_steps=steps, generator=generator, height=height, width=width).images[0], 
+      f"prompt: '{prompt}', seed = {int(seed)},\nheight: {height}px, width: {width}px,\nguidance: {guidance}, steps: {steps}"
       )