Merge pull request #179 from inverted-ai/upgrade-dependencies

Upgrade package dependencies

README.md

@@ -1,12 +1,16 @@
 [pypi-badge]: https://badge.fury.io/py/invertedai.svg
 [pypi-link]: https://pypi.org/project/invertedai/
+[python-badge]: https://img.shields.io/pypi/pyversions/invertedai.svg?color=%2334D058
+[ci-badge]: https://github.com/inverted-ai/invertedai/actions/workflows/CI.yml/badge.svg?branch=master
 [colab-badge]: https://colab.research.google.com/assets/colab-badge.svg
 [colab-link]: https://colab.research.google.com/github/inverted-ai/invertedai/blob/develop/examples/IAI_full_demo.ipynb
 [rest-link]: https://app.swaggerhub.com/apis-docs/InvertedAI/InvertedAI
 [examples-link]: https://github.com/inverted-ai/invertedai/tree/master/examples
 
 [![Documentation Status](https://readthedocs.org/projects/inverted-ai/badge/?version=latest)](https://inverted-ai.readthedocs.io/en/latest/?badge=latest)
 [![PyPI][pypi-badge]][pypi-link]
+[![python-badge]][pypi-link]
+[![ci-badge]](https://github.com/inverted-ai/invertedai/actions/workflows/CI.yml)
 [![Open In Colab][colab-badge]][colab-link]
 
 # InvertedAI

invertedai/api/drive.py

@@ -45,6 +45,7 @@ class DriveResponse(BaseModel):
     ]  #: For each agent, indicates whether the predicted state is inside supported area.
     traffic_lights_states: Optional[TrafficLightStatesDict] #: Traffic light states for the full map, each key-value pair corresponds to one particular traffic light.
     light_recurrent_states: Optional[LightRecurrentStates] #: Light recurrent states for the full map, each element corresponds to one light group.
+    api_model_version: str  # Model version used for this API call
 
 
 @validate_arguments
@@ -60,7 +61,7 @@ def drive(
         rendering_fov: Optional[float] = None,
         get_infractions: bool = False,
         random_seed: Optional[int] = None,
-        model_version: Optional[str] = None
+        api_model_version: Optional[str] = None
 ) -> DriveResponse:
     """
     Parameters
@@ -114,7 +115,7 @@ def drive(
     random_seed:
         Controls the stochastic aspects of agent behavior for reproducibility.
 
-    model_version:
+    api_model_version:
         Optionally specify the version of the model. If None is passed which is by default, the best model will be used.
     See Also
     --------
@@ -160,7 +161,7 @@ def _tolist(input_data: List):
         random_seed=random_seed,
         rendering_center=rendering_center,
         rendering_fov=rendering_fov,
-        model_version=model_version
+        model_version=api_model_version
     )
     start = time.time()
     timeout = TIMEOUT
@@ -186,7 +187,7 @@ def _tolist(input_data: List):
                 if response["infraction_indicators"]
                 else [],
                 is_inside_supported_area=response["is_inside_supported_area"],
-                model_version=response["model_version"],
+                api_model_version=response["model_version"],
                 traffic_lights_states=response["traffic_lights_states"]
                 if response["traffic_lights_states"] is not None 
                 else None,
@@ -219,7 +220,7 @@ async def async_drive(
         rendering_fov: Optional[float] = None,
         get_infractions: bool = False,
         random_seed: Optional[int] = None,
-        model_version: Optional[str] = None
+        api_model_versioin: Optional[str] = None
 ) -> DriveResponse:
     """
     A light async version of :func:`drive`
@@ -245,7 +246,7 @@ def _tolist(input_data: List):
         random_seed=random_seed,
         rendering_center=rendering_center,
         rendering_fov=rendering_fov,
-        model_version=model_version,
+        model_version=api_model_versioin,
     )
     response = await iai.session.async_request(model="drive", data=model_inputs)
 
@@ -266,7 +267,7 @@ def _tolist(input_data: List):
         if response["infraction_indicators"]
         else [],
         is_inside_supported_area=response["is_inside_supported_area"],
-        model_version=response["model_version"],
+        api_model_version=response["model_version"],
         traffic_lights_states=response["traffic_lights_states"] 
         if response["traffic_lights_states"] is not None 
         else None,

invertedai/api/initialize.py

@@ -1,5 +1,5 @@
 import time
-from pydantic import BaseModel, validate_arguments, root_validator
+from pydantic import BaseModel, validate_arguments
 from typing import List, Optional, Dict, Tuple
 import asyncio
 
@@ -45,7 +45,7 @@ class InitializeResponse(BaseModel):
     ]  #: If `get_infractions` was set, they are returned here.
     traffic_lights_states: Optional[TrafficLightStatesDict]  #: Traffic light states for the full map, each key-value pair corresponds to one particular traffic light.
     light_recurrent_states: Optional[LightRecurrentStates] #: Light recurrent states for the full map, each element corresponds to one light group.
-    model_version: str # Model version used for this API call
+    api_model_version: str # Model version used for this API call
 
 
 @validate_arguments
@@ -61,7 +61,7 @@ def initialize(
         get_infractions: bool = False,
         agent_count: Optional[int] = None,
         random_seed: Optional[int] = None,
-        model_version: Optional[str] = None  # Model version used for this API call
+        api_model_version: Optional[str] = None  # Model version used for this API call
 ) -> InitializeResponse:
     """
     Initializes a simulation in a given location, using a combination of **user-defined** and **sampled** agents.
@@ -116,7 +116,7 @@ def initialize(
     random_seed:
         Controls the stochastic aspects of initialization for reproducibility.
 
-    model_version:
+    api_model_version:
         Optionally specify the version of the model. If None is passed which is by default, the best model will be used.
 
     See Also
@@ -160,7 +160,7 @@ def initialize(
         location_of_interest=location_of_interest,
         get_infractions=get_infractions,
         random_seed=random_seed,
-        model_version=model_version
+        model_version=api_model_version
     )
     start = time.time()
     timeout = TIMEOUT
@@ -186,7 +186,7 @@ def initialize(
                 ]
                 if response["infraction_indicators"]
                 else [],
-                model_version=response["model_version"],
+                api_model_version=response["model_version"],
                 traffic_lights_states=response["traffic_lights_states"] 
                 if response["traffic_lights_states"] is not None 
                 else None,
@@ -217,7 +217,7 @@ async def async_initialize(
         get_infractions: bool = False,
         agent_count: Optional[int] = None,
         random_seed: Optional[int] = None,
-        model_version: Optional[str] = None
+        api_model_version: Optional[str] = None
 ) -> InitializeResponse:
     """
     The async version of :func:`initialize`
@@ -237,7 +237,7 @@ async def async_initialize(
         location_of_interest=location_of_interest,
         get_infractions=get_infractions,
         random_seed=random_seed,
-        model_version=model_version
+        model_version=api_model_version
     )
 
     response = await iai.session.async_request(model="initialize", data=model_inputs)
@@ -265,7 +265,7 @@ async def async_initialize(
         ]
         if response["infraction_indicators"]
         else [],
-        model_version=response["model_version"],
+        api_model_version=response["model_version"],
         traffic_lights_states=response["traffic_lights_states"]
         if response["traffic_lights_states"] is not None 
         else None,

invertedai/common.py

@@ -1,6 +1,6 @@
 from typing import List, Optional, Dict
 from enum import Enum
-from pydantic import BaseModel, root_validator
+from pydantic import BaseModel, model_validator
 import math
 
 import invertedai as iai
@@ -20,7 +20,7 @@ class RecurrentState(BaseModel):
 
     #: Internal representation of the recurrent state.
 
-    @root_validator
+    @model_validator(mode='before')
     @classmethod
     def check_recurrentstate(cls, values):
         if len(values.get("packed")) == RECURRENT_SIZE:

invertedai/utils.py

@@ -361,7 +361,7 @@ async def reinit(reinitialize_agent_state, reinitialize_agent_attrs, area_center
             file_path = f"{birdview_path}-{(area_center.x, area_center.y)}.jpg"
             response.birdview.decode_and_save(file_path)
 
-        return valid_agent_state, valid_agent_attrs, valid_agent_rs, response.model_version
+        return valid_agent_state, valid_agent_attrs, valid_agent_rs, response.api_model_version
 
     stride = initialize_fov / 2
 
@@ -404,7 +404,7 @@ async def reinit(reinitialize_agent_state, reinitialize_agent_attrs, area_center
         recurrent_states=new_recurrent_states,
         agent_states=new_agent_state,
         agent_attributes=new_attributes,
-        model_version=model_version
+        api_model_version=model_version
     )