small bug fixes in prompt generation

- fixes no closing quote in pretty-printed dream_prompt string
- removes unecessary -f switch when txt2img used

In addition, this commit does an experimental commenting-out of the
random.seed() call in the variation-generating part of ldm.dream.generator.base.
This fixes the problem of two calls that use the same seed and -v0.1
generating different images (invoke-ai#641). However, it does not fix the issue
of two images generated using the same seed and -VXXXXXX being
different.

ldm/dream/args.py

@@ -143,7 +143,7 @@ def dream_prompt_str(self,**kwargs):
         a = vars(self)
         a.update(kwargs)
         switches = list()
-        switches.append(f'"{a["prompt"]}')
+        switches.append(f'"{a["prompt"]}"')
         switches.append(f'-s {a["steps"]}')
         switches.append(f'-W {a["width"]}')
         switches.append(f'-H {a["height"]}')
@@ -152,15 +152,13 @@ def dream_prompt_str(self,**kwargs):
         switches.append(f'-S {a["seed"]}')
         if a['grid']:
             switches.append('--grid')
-        if a['iterations'] and a['iterations']>0:
-            switches.append(f'-n {a["iterations"]}')
         if a['seamless']:
             switches.append('--seamless')
         if a['init_img'] and len(a['init_img'])>0:
             switches.append(f'-I {a["init_img"]}')
         if a['fit']:
             switches.append(f'--fit')
-        if a['strength'] and a['strength']>0:
+        if a['init_img'] and a['strength'] and a['strength']>0:
             switches.append(f'-f {a["strength"]}')
         if a['gfpgan_strength']:
             switches.append(f'-G {a["gfpgan_strength"]}')

ldm/dream/generator/base.py

@@ -101,7 +101,7 @@ def generate_initial_noise(self, seed, width, height):
                 next_noise = self.get_noise(width,height)
                 initial_noise = self.slerp(v_weight, initial_noise, next_noise)
             if self.variation_amount > 0:
-                random.seed() # reset RNG to an actually random state, so we can get a random seed for variations
+#                random.seed() # reset RNG to an actually random state, so we can get a random seed for variations
                 seed = random.randrange(0,np.iinfo(np.uint32).max)
             return (seed, initial_noise)
         else: