remove torch and numpy dependencies

examples/Carla_Examples/Carla-Demo-Script-Birdview.py

@@ -5,7 +5,6 @@
 from PIL import Image as PImage
 import cv2
 import imageio
-import torch
 from dotenv import load_dotenv
 
 load_dotenv()
@@ -50,9 +49,9 @@
 
 for i in range(carla_cfg.episode_length * carla_cfg.fps):
     response = iai.drive(
-        agent_attributes=torch.tensor(dimensions).unsqueeze(0).tolist(),
-        states=torch.tensor(states).unsqueeze(0).tolist(),
-        recurrent_states=torch.tensor(recurrent_states).unsqueeze(0).tolist(),
+        agent_attributes=[dimensions],
+        states=[states],
+        recurrent_states=[recurrent_states],
         get_birdviews=True,
         location=args.scene_name,
         steps=1,

examples/Carla_Examples/Carla-Demo-Script.py

@@ -1,9 +1,6 @@
-import json
 import pygame
 import os
 import sys
-import numpy as np
-import torch
 from dotenv import load_dotenv
 
 load_dotenv()
@@ -60,9 +57,9 @@
 
 for i in range(carla_cfg.episode_length * carla_cfg.fps):
     response = iai.drive(
-        agent_attributes=torch.tensor(dimensions).unsqueeze(0).tolist(),
-        states=torch.tensor(states).unsqueeze(0).tolist(),
-        recurrent_states=torch.tensor(recurrent_states).unsqueeze(0).tolist(),
+        agent_attributes=[dimensions],
+        states=[states],
+        recurrent_states=[recurrent_states],
         location=args.scene_name,
         steps=1,
         traffic_states_id=response["traffic_states_id"],

examples/Carla_Examples/Carla-Demo.ipynb

@@ -10,7 +10,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 6,
    "id": "911445d4-8b61-49a1-9620-d1f3eb0c4199",
    "metadata": {},
    "outputs": [],
@@ -36,14 +36,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 7,
    "id": "069cf9cb-30eb-4378-b4f9-9cb7d9038620",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "dc706e042b09483395f47909abf289cb",
+       "model_id": "b967787e62ed43a7a536d3c075250bce",
        "version_major": 2,
        "version_minor": 0
       },
@@ -57,7 +57,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5dcc117e197c47f3821da0049c88ad9b",
+       "model_id": "3064400f5dd54fdc8754b9745f459be5",
        "version_major": 2,
        "version_minor": 0
       },
@@ -95,7 +95,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 8,
    "id": "94506da0-9a15-4dc0-9d57-5ac30bc36d72",
    "metadata": {},
    "outputs": [],
@@ -114,9 +114,9 @@
     "\n",
     "for i in range(carla_cfg.episode_length * carla_cfg.fps):\n",
     "    response = iai.drive(\n",
-    "        agent_attributes=torch.tensor(dimensions).unsqueeze(0).tolist(),\n",
-    "        states=torch.tensor(states).unsqueeze(0).tolist(),\n",
-    "        recurrent_states=torch.tensor(recurrent_states).unsqueeze(0).tolist(),\n",
+    "        agent_attributes=[dimensions],\n",
+    "        states=[states],\n",
+    "        recurrent_states=[recurrent_states],\n",
     "        get_birdviews=True,\n",
     "        location=scene_name,\n",
     "        steps=1,\n",
@@ -132,7 +132,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 9,
    "id": "adaf461b-b846-40bc-835d-171466aaf508",
    "metadata": {},
    "outputs": [],

examples/Carla_Examples/Carla-Scenario.py

@@ -1,9 +1,7 @@
-import json
 import pygame
 import os
 import sys
 import numpy as np
-import torch
 from dotenv import load_dotenv
 
 load_dotenv()
@@ -60,9 +58,9 @@
     states, recurrent_states, dimensions = sim.reset()
     for i in range(carla_cfg.episode_length * carla_cfg.fps):
         response = iai.drive(
-            agent_attributes=torch.tensor(dimensions).unsqueeze(0).tolist(),
-            states=torch.tensor(states).unsqueeze(0).tolist(),
-            recurrent_states=torch.tensor(recurrent_states).unsqueeze(0).tolist(),
+            agent_attributes=[dimensions],
+            states=[states],
+            recurrent_states=[recurrent_states],
             location=args.scene_name,
             steps=1,
             traffic_states_id=response["traffic_states_id"],

invertedai/api_resources.py

@@ -1,15 +1,12 @@
 from invertedai.error import TryAgain
-from dataclasses import dataclass
-import numpy as np
-from typing import List, Union, Optional
+import math
+from typing import List, Optional
 import time
 import invertedai as iai
 
 
 TIMEOUT = 10
 
-InputDataType = Union[np.ndarray, np.ndarray, List]
-
 
 def initialize(
     location="CARLA:Town03:Roundabout",
@@ -27,8 +24,8 @@ def initialize(
                 "location": location,
                 "num_agents_to_spawn": agent_count,
                 "num_samples": batch_size,
-                "spawn_min_speed": min_speed and np.ceil(min_speed / 3.6).astype(int),
-                "spawn_max_speed": max_speed and np.ceil(max_speed / 3.6).astype(int),
+                "spawn_min_speed": min_speed and int(math.ceil(min_speed / 3.6)),
+                "spawn_max_speed": max_speed and int(math.ceil(max_speed / 3.6)),
             }
             initial_states = iai.session.request(model="initialize", params=params)
             response = {
@@ -48,15 +45,15 @@ def initialize(
 def drive(
     states: dict,
     agent_attributes: dict,
-    recurrent_states: Optional[InputDataType] = None,
+    recurrent_states: Optional[List] = None,
     get_birdviews: bool = False,
     location="CARLA:Town03:Roundabout",
     steps: int = 1,
     get_infractions: bool = False,
     traffic_states_id: str = "000:0",
     exclude_ego_agent: bool = True,
 ) -> dict:
-    def _tolist(input_data: InputDataType):
+    def _tolist(input_data: List):
         if not isinstance(input_data, list):
             return input_data.tolist()
         else:

invertedai/models.py

@@ -1,6 +1,5 @@
 from dataclasses import dataclass
 from typing import List
-from torch import Tensor
 
 
 @dataclass

invertedai/utils.py

@@ -2,7 +2,6 @@
 import json
 import re
 from typing import Dict, Optional
-import numpy as np
 from requests.auth import AuthBase
 import invertedai as iai
 from invertedai import error
@@ -183,6 +182,7 @@ def __call__(self, r):
 def Jupyter_Render():
     import ipywidgets as widgets
     import matplotlib.pyplot as plt
+    import numpy as np
 
     class Jupyter_Render(widgets.HBox):
         def __init__(self):

pyproject.toml

@@ -12,9 +12,9 @@ packages = [
 [tool.poetry.dependencies]
 python = ">=3.7,<3.11"
 python-dotenv = "^0.21.0"
-numpy = "^1.17.0"
 
 [tool.poetry.group.dev.dependencies]
+numpy = "^1.17.0"
 matplotlib = "^3.5"
 ipython = "^7.34"
 ipywidgets = "^8.0.2"