Fix typos and minor redundancies (open-mmlab#2029)

fix typos and minor redundancies

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_img2img.py

@@ -397,7 +397,7 @@ def check_inputs(self, prompt, strength, callback_steps):
  raise ValueError(f"`prompt` has to be of type `str` or `list` but is {type(prompt)}")
 
  if strength < 0 or strength > 1:
- raise ValueError(f"The value of strength should in [1.0, 1.0] but is {strength}")
+ raise ValueError(f"The value of strength should in [0.0, 1.0] but is {strength}")
 
  if (callback_steps is None) or (
  callback_steps is not None and (not isinstance(callback_steps, int) or callback_steps <= 0)

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_upscale.py

@@ -499,7 +499,7 @@ def __call__(
  # perform guidance
  if do_classifier_free_guidance:
  noise_pred_uncond, noise_pred_text = noise_pred.chunk(2)
- noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_uncond)
+  noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_uncond)
 
  # compute the previous noisy sample x_t -> x_t-1
  latents = self.scheduler.step(noise_pred, t, latents, **extra_step_kwargs).prev_sample

src/diffusers/schedulers/scheduling_ddim.py

@@ -327,7 +327,7 @@ def step(
  variance_noise = randn_tensor(
  model_output.shape, generator=generator, device=device, dtype=model_output.dtype
  )
- variance = self._get_variance(timestep, prev_timestep) ** (0.5) * eta * variance_noise
+ variance = std_dev_t * variance_noise
 
  prev_sample = prev_sample + variance