






"""simple docstring"""






import darl  # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline


UpperCAmelCase_   : Optional[int]   			= {
    """n_samples""": 64,
    """horizon""": 32,
    """num_inference_steps""": 20,
    """n_guide_steps""": 2,  # can set to 0 for faster sampling, does not use value network
    """scale_grad_by_std""": True,
    """scale""": 0.1,
    """eta""": 0.0,
    """t_grad_cutoff""": 2,
    """device""": """cpu""",
}


if __name__ == "__main__":
  UpperCAmelCase_   : str   			= """hopper-medium-v2"""
  UpperCAmelCase_   : int   			= gym.make(env_name)

  UpperCAmelCase_   : Any   			= ValueGuidedRLPipeline.from_pretrained(
      """bglick13/hopper-medium-v2-value-function-hor32""",
      env=env,
  )

  env.seed(0)
  UpperCAmelCase_   : Optional[int]   			= env.reset()
  UpperCAmelCase_   : str   			= 0
  UpperCAmelCase_   : List[Any]   			= 0
  UpperCAmelCase_   : List[str]   			= 1000
  UpperCAmelCase_   : List[str]   			= [obs.copy()]
  try:
    for t in tqdm.tqdm(range(T)):
      # call the policy
      UpperCAmelCase_   : Dict   			= pipeline(obs, planning_horizon=32)

      # execute action in environment
      UpperCAmelCase_			,  UpperCAmelCase_			,  UpperCAmelCase_			,  UpperCAmelCase_   : int   			= env.step(denorm_actions)
      UpperCAmelCase_   : Union[str, Any]   			= env.get_normalized_score(total_reward)

      # update return
      total_reward += reward
      total_score += score
      print(
          f'''Step: {t}, Reward: {reward}, Total Reward: {total_reward}, Score: {score}, Total Score:'''
          f''' {total_score}'''
      )

      # save observations for rendering
      rollout.append(next_observation.copy())

      UpperCAmelCase_   : int   			= next_observation
  except KeyboardInterrupt:
    pass

  print(f'''Total reward: {total_reward}''')










"""simple docstring"""






import unittest

from diffusers.pipelines.pipeline_utils import is_safetensors_compatible




class 							lowerCAmelCase__				(			unittest.TestCase ):






      '''simple docstring'''

      def _SCREAMING_SNAKE_CASE (						self     :  str):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Optional[Any]    						=		[
              '''safety_checker/pytorch_model.bin''',
              '''safety_checker/model.safetensors''',
              '''vae/diffusion_pytorch_model.bin''',
              '''vae/diffusion_pytorch_model.safetensors''',
              '''text_encoder/pytorch_model.bin''',
              '''text_encoder/model.safetensors''',
              '''unet/diffusion_pytorch_model.bin''',
              '''unet/diffusion_pytorch_model.safetensors''',
          ]
          self.assertTrue(is_safetensors_compatible(lowercase_))
      def _SCREAMING_SNAKE_CASE (						self     :  Optional[int]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Optional[Any]    						=		[
              '''unet/diffusion_pytorch_model.bin''',
              '''unet/diffusion_pytorch_model.safetensors''',
          ]
          self.assertTrue(is_safetensors_compatible(lowercase_))
      def _SCREAMING_SNAKE_CASE (						self     :  List[str]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Optional[int]    						=		[
              '''safety_checker/pytorch_model.bin''',
              '''safety_checker/model.safetensors''',
              '''vae/diffusion_pytorch_model.bin''',
              '''vae/diffusion_pytorch_model.safetensors''',
              '''text_encoder/pytorch_model.bin''',
              '''text_encoder/model.safetensors''',
              '''unet/diffusion_pytorch_model.bin''',
              # Removed: 'unet/diffusion_pytorch_model.safetensors',
          ]
          self.assertFalse(is_safetensors_compatible(lowercase_))
      def _SCREAMING_SNAKE_CASE (						self     :  int):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  List[Any]    						=		[
              '''text_encoder/pytorch_model.bin''',
              '''text_encoder/model.safetensors''',
          ]
          self.assertTrue(is_safetensors_compatible(lowercase_))
      def _SCREAMING_SNAKE_CASE (						self     :  Optional[int]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Optional[int]    						=		[
              '''safety_checker/pytorch_model.bin''',
              '''safety_checker/model.safetensors''',
              '''vae/diffusion_pytorch_model.bin''',
              '''vae/diffusion_pytorch_model.safetensors''',
              '''text_encoder/pytorch_model.bin''',
              # Removed: 'text_encoder/model.safetensors',
              '''unet/diffusion_pytorch_model.bin''',
              '''unet/diffusion_pytorch_model.safetensors''',
          ]
          self.assertFalse(is_safetensors_compatible(lowercase_))
      def _SCREAMING_SNAKE_CASE (						self     :  List[Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  str    						=		[
              '''safety_checker/pytorch_model.fp16.bin''',
              '''safety_checker/model.fp16.safetensors''',
              '''vae/diffusion_pytorch_model.fp16.bin''',
              '''vae/diffusion_pytorch_model.fp16.safetensors''',
              '''text_encoder/pytorch_model.fp16.bin''',
              '''text_encoder/model.fp16.safetensors''',
              '''unet/diffusion_pytorch_model.fp16.bin''',
              '''unet/diffusion_pytorch_model.fp16.safetensors''',
          ]
          SCREAMING_SNAKE_CASE_      :  Any    						=		'''fp16'''
          self.assertTrue(is_safetensors_compatible(lowercase_						,	variant=lowercase_))
      def _SCREAMING_SNAKE_CASE (						self     :  str):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Optional[int]    						=		[
              '''unet/diffusion_pytorch_model.fp16.bin''',
              '''unet/diffusion_pytorch_model.fp16.safetensors''',
          ]
          SCREAMING_SNAKE_CASE_      :  Dict    						=		'''fp16'''
          self.assertTrue(is_safetensors_compatible(lowercase_						,	variant=lowercase_))
      def _SCREAMING_SNAKE_CASE (						self     :  int):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  List[str]    						=		[
              '''unet/diffusion_pytorch_model.bin''',
              '''unet/diffusion_pytorch_model.safetensors''',
          ]
          SCREAMING_SNAKE_CASE_      :  Any    						=		'''fp16'''
          self.assertTrue(is_safetensors_compatible(lowercase_						,	variant=lowercase_))
      def _SCREAMING_SNAKE_CASE (						self     :  Union[str, Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Tuple    						=		[
              '''safety_checker/pytorch_model.fp16.bin''',
              '''safety_checker/model.fp16.safetensors''',
              '''vae/diffusion_pytorch_model.fp16.bin''',
              '''vae/diffusion_pytorch_model.fp16.safetensors''',
              '''text_encoder/pytorch_model.fp16.bin''',
              '''text_encoder/model.fp16.safetensors''',
              '''unet/diffusion_pytorch_model.fp16.bin''',
              # Removed: 'unet/diffusion_pytorch_model.fp16.safetensors',
          ]
          SCREAMING_SNAKE_CASE_      :  List[Any]    						=		'''fp16'''
          self.assertFalse(is_safetensors_compatible(lowercase_						,	variant=lowercase_))
      def _SCREAMING_SNAKE_CASE (						self     :  List[Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  List[Any]    						=		[
              '''text_encoder/pytorch_model.fp16.bin''',
              '''text_encoder/model.fp16.safetensors''',
          ]
          SCREAMING_SNAKE_CASE_      :  Any    						=		'''fp16'''
          self.assertTrue(is_safetensors_compatible(lowercase_						,	variant=lowercase_))
      def _SCREAMING_SNAKE_CASE (						self     :  List[str]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Optional[Any]    						=		[
              '''text_encoder/pytorch_model.bin''',
              '''text_encoder/model.safetensors''',
          ]
          SCREAMING_SNAKE_CASE_      :  List[Any]    						=		'''fp16'''
          self.assertTrue(is_safetensors_compatible(lowercase_						,	variant=lowercase_))



      def _SCREAMING_SNAKE_CASE (						self     :  Optional[Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Optional[int]    						=		[
              '''safety_checker/pytorch_model.fp16.bin''',
              '''safety_checker/model.fp16.safetensors''',
              '''vae/diffusion_pytorch_model.fp16.bin''',
              '''vae/diffusion_pytorch_model.fp16.safetensors''',
              '''text_encoder/pytorch_model.fp16.bin''',
              # 'text_encoder/model.fp16.safetensors',
              '''unet/diffusion_pytorch_model.fp16.bin''',
              '''unet/diffusion_pytorch_model.fp16.safetensors''',
          ]
          SCREAMING_SNAKE_CASE_      :  str    						=		'''fp16'''
          self.assertFalse(is_safetensors_compatible(lowercase_						,	variant=lowercase_))


