
"""simple docstring"""




from __future__ import annotations

import unittest
from collections.abc import Iterator




class 					UpperCamelCase     :

				"""simple docstring"""



				def __init__(    self		,     lowercase__		,     lowercase__      )   ->   None:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     label
									SCREAMING_SNAKE_CASE           =     parent
									SCREAMING_SNAKE_CASE           =     None
									SCREAMING_SNAKE_CASE           =     None






class 					UpperCamelCase     :

				"""simple docstring"""



				def __init__(    self      )   ->   None:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     None


				def 							A (    self      )   ->   None:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     None


				def 							A (    self      )   ->   bool:
									"""simple docstring"""







									return self.root is None


				def 							A (    self		,     lowercase__      )   ->   None:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self._put(self.root		,     lowercase__      )


				def 							A (    self		,     lowercase__		,     lowercase__		,     lowercase__ = None      )   ->   Node:
									"""simple docstring"""







									if node is None:
														SCREAMING_SNAKE_CASE           =     Node(lowercase__		,     lowercase__      )
									else:
														if label < node.label:
																			SCREAMING_SNAKE_CASE           =     self._put(node.left		,     lowercase__		,     lowercase__      )
														elif label > node.label:
																			SCREAMING_SNAKE_CASE           =     self._put(node.right		,     lowercase__		,     lowercase__      )
														else:
																			SCREAMING_SNAKE_CASE           =     f'''Node with label {label} already exists'''
																			raise Exception(lowercase__      )

									return node


				def 							A (    self		,     lowercase__      )   ->   Node:
									"""simple docstring"""







									return self._search(self.root		,     lowercase__      )


				def 							A (    self		,     lowercase__		,     lowercase__      )   ->   Node:
									"""simple docstring"""







									if node is None:
														SCREAMING_SNAKE_CASE           =     f'''Node with label {label} does not exist'''
														raise Exception(lowercase__      )
									else:
														if label < node.label:
																			SCREAMING_SNAKE_CASE           =     self._search(node.left		,     lowercase__      )
														elif label > node.label:
																			SCREAMING_SNAKE_CASE           =     self._search(node.right		,     lowercase__      )

									return node


				def 							A (    self		,     lowercase__      )   ->   None:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self.search(lowercase__      )
									if node.right and node.left:
														SCREAMING_SNAKE_CASE           =     self._get_lowest_node(node.right      )
														SCREAMING_SNAKE_CASE           =     node.left
														SCREAMING_SNAKE_CASE           =     node.right
														SCREAMING_SNAKE_CASE           =     lowest_node
														if node.right:
																			SCREAMING_SNAKE_CASE           =     lowest_node
														self._reassign_nodes(lowercase__		,     lowercase__      )
									elif not node.right and node.left:
														self._reassign_nodes(lowercase__		,     node.left      )
									elif node.right and not node.left:
														self._reassign_nodes(lowercase__		,     node.right      )
									else:
														self._reassign_nodes(lowercase__		,     lowercase__      )


				def 							A (    self		,     lowercase__		,     lowercase__      )   ->   None:
									"""simple docstring"""







									if new_children:
														SCREAMING_SNAKE_CASE           =     node.parent

									if node.parent:
														if node.parent.right == node:
																			SCREAMING_SNAKE_CASE           =     new_children
														else:
																			SCREAMING_SNAKE_CASE           =     new_children
									else:
														SCREAMING_SNAKE_CASE           =     new_children


				def 							A (    self		,     lowercase__      )   ->   Node:
									"""simple docstring"""







									if node.left:
														SCREAMING_SNAKE_CASE           =     self._get_lowest_node(node.left      )
									else:
														SCREAMING_SNAKE_CASE           =     node
														self._reassign_nodes(lowercase__		,     node.right      )

									return lowest_node


				def 							A (    self		,     lowercase__      )   ->   bool:
									"""simple docstring"""







									try:
														self.search(lowercase__      )
														return True
									except Exception:
														return False


				def 							A (    self      )   ->   int:
									"""simple docstring"""







									if self.root is None:
														raise Exception('Binary search tree is empty'      )

									SCREAMING_SNAKE_CASE           =     self.root
									while node.right is not None:
														SCREAMING_SNAKE_CASE           =     node.right

									return node.label


				def 							A (    self      )   ->   int:
									"""simple docstring"""







									if self.root is None:
														raise Exception('Binary search tree is empty'      )

									SCREAMING_SNAKE_CASE           =     self.root
									while node.left is not None:
														SCREAMING_SNAKE_CASE           =     node.left

									return node.label


				def 							A (    self      )   ->   Iterator[Node]:
									"""simple docstring"""







									return self._inorder_traversal(self.root      )


				def 							A (    self		,     lowercase__      )   ->   Iterator[Node]:
									"""simple docstring"""







									if node is not None:
														yield from self._inorder_traversal(node.left      )
														yield node
														yield from self._inorder_traversal(node.right      )


				def 							A (    self      )   ->   Iterator[Node]:
									"""simple docstring"""







									return self._preorder_traversal(self.root      )




				def 							A (    self		,     lowercase__      )   ->   Iterator[Node]:
									"""simple docstring"""







									if node is not None:
														yield node
														yield from self._preorder_traversal(node.left      )
														yield from self._preorder_traversal(node.right      )






class 					UpperCamelCase     (	unittest.TestCase				):

				"""simple docstring"""



				@staticmethod
				def 							A (    )   ->   BinarySearchTree:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     BinarySearchTree()
									t.put(8      )
									t.put(3      )
									t.put(6      )
									t.put(1      )
									t.put(10      )
									t.put(14      )
									t.put(13      )
									t.put(4      )
									t.put(7      )
									t.put(5      )

									return t


				def 							A (    self      )   ->   None:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     BinarySearchTree()
									assert t.is_empty()

									t.put(8      )
									assert t.root is not None
									assert t.root.parent is None
									assert t.root.label == 8

									t.put(10      )
									assert t.root.right is not None
									assert t.root.right.parent == t.root
									assert t.root.right.label == 10

									t.put(3      )
									assert t.root.left is not None
									assert t.root.left.parent == t.root
									assert t.root.left.label == 3

									t.put(6      )
									assert t.root.left.right is not None
									assert t.root.left.right.parent == t.root.left
									assert t.root.left.right.label == 6

									t.put(1      )
									assert t.root.left.left is not None
									assert t.root.left.left.parent == t.root.left
									assert t.root.left.left.label == 1

									with self.assertRaises(lowercase__      ):  # noqa: B017
														t.put(1      )


				def 							A (    self      )   ->   None:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self._get_binary_search_tree()

									SCREAMING_SNAKE_CASE           =     t.search(6      )
									assert node.label == 6

									SCREAMING_SNAKE_CASE           =     t.search(13      )
									assert node.label == 13

									with self.assertRaises(lowercase__      ):  # noqa: B017
														t.search(2      )


				def 							A (    self      )   ->   None:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self._get_binary_search_tree()

									t.remove(13      )
									assert t.root is not None
									assert t.root.right is not None
									assert t.root.right.right is not None
									assert t.root.right.right.right is None
									assert t.root.right.right.left is None

									t.remove(7      )
									assert t.root.left is not None
									assert t.root.left.right is not None
									assert t.root.left.right.left is not None
									assert t.root.left.right.right is None
									assert t.root.left.right.left.label == 4

									t.remove(6      )
									assert t.root.left.left is not None
									assert t.root.left.right.right is not None
									assert t.root.left.left.label == 1
									assert t.root.left.right.label == 4
									assert t.root.left.right.right.label == 5
									assert t.root.left.right.left is None
									assert t.root.left.left.parent == t.root.left
									assert t.root.left.right.parent == t.root.left

									t.remove(3      )
									assert t.root is not None
									assert t.root.left.label == 4
									assert t.root.left.right.label == 5
									assert t.root.left.left.label == 1
									assert t.root.left.parent == t.root
									assert t.root.left.left.parent == t.root.left
									assert t.root.left.right.parent == t.root.left

									t.remove(4      )
									assert t.root.left is not None
									assert t.root.left.left is not None
									assert t.root.left.label == 5
									assert t.root.left.right is None
									assert t.root.left.left.label == 1
									assert t.root.left.parent == t.root
									assert t.root.left.left.parent == t.root.left


				def 							A (    self      )   ->   None:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self._get_binary_search_tree()

									t.remove(3      )
									assert t.root is not None
									assert t.root.left is not None
									assert t.root.left.left is not None
									assert t.root.left.right is not None
									assert t.root.left.right.left is not None
									assert t.root.left.right.right is not None
									assert t.root.left.label == 4
									assert t.root.left.right.label == 6
									assert t.root.left.left.label == 1
									assert t.root.left.right.right.label == 7
									assert t.root.left.right.left.label == 5
									assert t.root.left.parent == t.root
									assert t.root.left.right.parent == t.root.left
									assert t.root.left.left.parent == t.root.left
									assert t.root.left.right.left.parent == t.root.left.right


				def 							A (    self      )   ->   None:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self._get_binary_search_tree()
									t.empty()
									assert t.root is None


				def 							A (    self      )   ->   None:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self._get_binary_search_tree()
									assert not t.is_empty()

									t.empty()
									assert t.is_empty()


				def 							A (    self      )   ->   None:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self._get_binary_search_tree()

									assert t.exists(6      )
									assert not t.exists(-1      )


				def 							A (    self      )   ->   None:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self._get_binary_search_tree()

									assert t.get_max_label() == 14

									t.empty()
									with self.assertRaises(lowercase__      ):  # noqa: B017
														t.get_max_label()


				def 							A (    self      )   ->   None:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self._get_binary_search_tree()

									assert t.get_min_label() == 1

									t.empty()
									with self.assertRaises(lowercase__      ):  # noqa: B017
														t.get_min_label()


				def 							A (    self      )   ->   None:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self._get_binary_search_tree()

									SCREAMING_SNAKE_CASE           =     [i.label for i in t.inorder_traversal()]
									assert inorder_traversal_nodes == [1, 3, 4, 5, 6, 7, 8, 10, 13, 14]




				def 							A (    self      )   ->   None:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =     self._get_binary_search_tree()

									SCREAMING_SNAKE_CASE           =     [i.label for i in t.preorder_traversal()]
									assert preorder_traversal_nodes == [8, 3, 1, 6, 4, 5, 7, 10, 14, 13]






def   UpperCamelCase_  (		):
					SCREAMING_SNAKE_CASE           =     BinarySearchTree()
					t.put(8      )
					t.put(3      )
					t.put(6      )
					t.put(1      )
					t.put(1_0      )
					t.put(1_4      )
					t.put(1_3      )
					t.put(4      )
					t.put(7      )
					t.put(5      )

					print(
					    '\n            8\n           / \\\n          3   10\n         / \\    \\\n        1   6    14\n           / \\   /\n          4   7 13\n           \\\n            5\n        '      )

					print('Label 6 exists:',					t.exists(6      )      )
					print('Label 13 exists:',					t.exists(1_3      )      )
					print('Label -1 exists:',					t.exists(-1      )      )
					print('Label 12 exists:',					t.exists(1_2      )      )

					# Prints all the elements of the list in inorder traversal
					SCREAMING_SNAKE_CASE           =     [i.label for i in t.inorder_traversal()]
					print('Inorder traversal:',					SCREAMING_SNAKE_CASE_      )

					# Prints all the elements of the list in preorder traversal
					SCREAMING_SNAKE_CASE           =     [i.label for i in t.preorder_traversal()]
					print('Preorder traversal:',					SCREAMING_SNAKE_CASE_      )

					print('Max. label:',					t.get_max_label()      )
					print('Min. label:',					t.get_min_label()      )

					# Delete elements
					print('\nDeleting elements 13, 10, 8, 3, 6, 14'      )
					print(
					    '\n          4\n         / \\\n        1   7\n             \\\n              5\n        '      )
					t.remove(1_3      )
					t.remove(1_0      )
					t.remove(8      )
					t.remove(3      )
					t.remove(6      )
					t.remove(1_4      )

					# Prints all the elements of the list in inorder traversal after delete
					SCREAMING_SNAKE_CASE           =     [i.label for i in t.inorder_traversal()]
					print('Inorder traversal after delete:',					SCREAMING_SNAKE_CASE_      )

					# Prints all the elements of the list in preorder traversal after delete
					SCREAMING_SNAKE_CASE           =     [i.label for i in t.preorder_traversal()]
					print('Preorder traversal after delete:',					SCREAMING_SNAKE_CASE_      )

					print('Max. label:',					t.get_max_label()      )
					print('Min. label:',					t.get_min_label()      )


if __name__ == "__main__":
	binary_search_tree_example()


"""simple docstring"""




import gym
import numpy as np
import torch
from mujoco_py import GlfwContext

from transformers import DecisionTransformerModel


GlfwContext(offscreen=True)  # Create a window to init GLFW.

def   UpperCamelCase_  (		SCREAMING_SNAKE_CASE_,					SCREAMING_SNAKE_CASE_,					SCREAMING_SNAKE_CASE_,					SCREAMING_SNAKE_CASE_,					SCREAMING_SNAKE_CASE_,					SCREAMING_SNAKE_CASE_      ):
					# we don't care about the past rewards in this model

					SCREAMING_SNAKE_CASE           =     states.reshape(1,					-1,					model.config.state_dim      )
					SCREAMING_SNAKE_CASE           =     actions.reshape(1,					-1,					model.config.act_dim      )
					SCREAMING_SNAKE_CASE           =     returns_to_go.reshape(1,					-1,					1      )
					SCREAMING_SNAKE_CASE           =     timesteps.reshape(1,					-1      )

					if model.config.max_length is not None:
										SCREAMING_SNAKE_CASE           =     states[:, -model.config.max_length :]
										SCREAMING_SNAKE_CASE           =     actions[:, -model.config.max_length :]
										SCREAMING_SNAKE_CASE           =     returns_to_go[:, -model.config.max_length :]
										SCREAMING_SNAKE_CASE           =     timesteps[:, -model.config.max_length :]

										# pad all tokens to sequence length
										SCREAMING_SNAKE_CASE           =     torch.cat(
										    [torch.zeros(model.config.max_length - states.shape[1]      ), torch.ones(states.shape[1]      )]      )
										SCREAMING_SNAKE_CASE           =     attention_mask.to(dtype=torch.long,					device=states.device      ).reshape(1,					-1      )
										SCREAMING_SNAKE_CASE           =     torch.cat(
										    [
										        torch.zeros(
										            (states.shape[0], model.config.max_length - states.shape[1], model.config.state_dim),					device=states.device,					),
										        states,
										    ],					dim=1,					).to(dtype=torch.floataa      )
										SCREAMING_SNAKE_CASE           =     torch.cat(
										    [
										        torch.zeros(
										            (actions.shape[0], model.config.max_length - actions.shape[1], model.config.act_dim),					device=actions.device,					),
										        actions,
										    ],					dim=1,					).to(dtype=torch.floataa      )
										SCREAMING_SNAKE_CASE           =     torch.cat(
										    [
										        torch.zeros(
										            (returns_to_go.shape[0], model.config.max_length - returns_to_go.shape[1], 1),					device=returns_to_go.device,					),
										        returns_to_go,
										    ],					dim=1,					).to(dtype=torch.floataa      )
										SCREAMING_SNAKE_CASE           =     torch.cat(
										    [
										        torch.zeros(
										            (timesteps.shape[0], model.config.max_length - timesteps.shape[1]),					device=timesteps.device      ),
										        timesteps,
										    ],					dim=1,					).to(dtype=torch.long      )
					else:
										SCREAMING_SNAKE_CASE           =     None

					SCREAMING_SNAKE_CASE     ,   SCREAMING_SNAKE_CASE     ,   SCREAMING_SNAKE_CASE           =     model(
					    states=SCREAMING_SNAKE_CASE_,					actions=SCREAMING_SNAKE_CASE_,					rewards=SCREAMING_SNAKE_CASE_,					returns_to_go=SCREAMING_SNAKE_CASE_,					timesteps=SCREAMING_SNAKE_CASE_,					attention_mask=SCREAMING_SNAKE_CASE_,					return_dict=SCREAMING_SNAKE_CASE_,					)

					return action_preds[0, -1]


# build the environment

snake_case			       =		gym.make('Hopper-v3')
snake_case			       =		env.observation_space.shape[0]
snake_case			       =		env.action_space.shape[0]
snake_case			       =		1_0_0_0
snake_case			       =		'cuda'
snake_case			       =		1_0_0_0.0  # normalization for rewards/returns
snake_case			       =		3_6_0_0 / scale  # evaluation conditioning targets, 3600 is reasonable from the paper LINK
snake_case			       =		np.array(
    [
        1.3_1_1_2_7_9,
        -0.0_8_4_6_9_5_2_1,
        -0.5_3_8_2_7_1_9,
        -0.0_7_2_0_1_5_7_6,
        0.0_4_9_3_2_3_6_6,
        2.1_0_6_6_8_5_6,
        -0.1_5_0_1_7_3_5_4,
        0.0_0_8_7_8_3_4_5,
        -0.2_8_4_8_1_8_6,
        -0.1_8_5_4_0_0_9_6,
        -0.2_8_4_6_1_2_8_6,
    ]
)
snake_case			       =		np.array(
    [
        0.1_7_7_9_0_7_5_1,
        0.0_5_4_4_4_6_2_1,
        0.2_1_2_9_7_1_3_9,
        0.1_4_5_3_0_4_1_9,
        0.6_1_2_4_4_4_4,
        0.8_5_1_7_4_4_6_5,
        1.4_5_1_5_2_5_2,
        0.6_7_5_1_6_9_6,
        1.5_3_6_2_3_9,
        1.6_1_6_0_7_4_6,
        5.6_0_7_2_5_3_6,
    ]
)
snake_case			       =		torch.from_numpy(state_mean).to(device=device)
snake_case			       =		torch.from_numpy(state_std).to(device=device)

# Create the decision transformer model
snake_case			       =		DecisionTransformerModel.from_pretrained('edbeeching/decision-transformer-gym-hopper-medium')
snake_case			       =		model.to(device)
model.eval()

for ep in range(1_0):
	snake_case       ,      snake_case			       =		0, 0
	snake_case			       =		env.reset()
	snake_case			       =		torch.tensor(TARGET_RETURN, device=device, dtype=torch.floataa).reshape(1, 1)
	snake_case			       =		torch.from_numpy(state).reshape(1, state_dim).to(device=device, dtype=torch.floataa)
	snake_case			       =		torch.zeros((0, act_dim), device=device, dtype=torch.floataa)
	snake_case			       =		torch.zeros(0, device=device, dtype=torch.floataa)

	snake_case			       =		torch.tensor(0, device=device, dtype=torch.long).reshape(1, 1)
	for t in range(max_ep_len):
		env.render()
		# add padding
		snake_case			       =		torch.cat([actions, torch.zeros((1, act_dim), device=device)], dim=0)
		snake_case			       =		torch.cat([rewards, torch.zeros(1, device=device)])

		snake_case			       =		get_action(
		    model,
		    (states.to(dtype=torch.floataa) - state_mean) / state_std,
		    actions.to(dtype=torch.floataa),
		    rewards.to(dtype=torch.floataa),
		    target_return.to(dtype=torch.floataa),
		    timesteps.to(dtype=torch.long),
		)
		snake_case			       =		action
		snake_case			       =		action.detach().cpu().numpy()

		snake_case       ,      snake_case       ,      snake_case       ,      snake_case			       =		env.step(action)

		snake_case			       =		torch.from_numpy(state).to(device=device).reshape(1, state_dim)
		snake_case			       =		torch.cat([states, cur_state], dim=0)
		snake_case			       =		reward

		snake_case			       =		target_return[0, -1] - (reward / scale)
		snake_case			       =		torch.cat([target_return, pred_return.reshape(1, 1)], dim=1)
		snake_case			       =		torch.cat([timesteps, torch.ones((1, 1), device=device, dtype=torch.long) * (t + 1)], dim=1)

		episode_return += reward
		episode_length += 1

		if done:
			break
