From 4a8b5be0d18f13b0637447fe0f7d18204e2d7434 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrick=20Sodr=C3=A9?= <psodre@gmail.com>
Date: Tue, 2 Nov 2021 05:21:40 +0000
Subject: [PATCH 01/16] Initial version of DarkNet for SM Toolkit

---
 .gitignore                                    |  6 ++
 Vagrantfile                                   | 91 +++++++++++++++++++
 environment.yml                               | 11 ++-
 setup.py                                      | 11 ++-
 src/darknet/py/__init__.py                    |  3 +-
 src/darknet/sagemaker/__init__.py             |  4 +
 src/darknet/sagemaker/__main__.py             | 29 ++++++
 src/darknet/sagemaker/classifier/__init__.py  |  3 +
 src/darknet/sagemaker/classifier/__main__.py  | 28 ++++++
 .../classifier/default_inference_handler.py   | 38 ++++++++
 .../sagemaker/classifier/handler_service.py   | 19 ++++
 .../sagemaker/default_inference_handler.py    | 43 +++++++++
 src/darknet/sagemaker/detector/__init__.py    |  3 +
 src/darknet/sagemaker/detector/__main__.py    | 27 ++++++
 .../detector/default_inference_handler.py     | 42 +++++++++
 .../sagemaker/detector/handler_service.py     | 19 ++++
 16 files changed, 373 insertions(+), 4 deletions(-)
 create mode 100644 Vagrantfile
 create mode 100644 src/darknet/sagemaker/__init__.py
 create mode 100644 src/darknet/sagemaker/__main__.py
 create mode 100644 src/darknet/sagemaker/classifier/__init__.py
 create mode 100644 src/darknet/sagemaker/classifier/__main__.py
 create mode 100644 src/darknet/sagemaker/classifier/default_inference_handler.py
 create mode 100644 src/darknet/sagemaker/classifier/handler_service.py
 create mode 100644 src/darknet/sagemaker/default_inference_handler.py
 create mode 100644 src/darknet/sagemaker/detector/__init__.py
 create mode 100644 src/darknet/sagemaker/detector/__main__.py
 create mode 100644 src/darknet/sagemaker/detector/default_inference_handler.py
 create mode 100644 src/darknet/sagemaker/detector/handler_service.py

diff --git a/.gitignore b/.gitignore
index df17089..c1fbd07 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,3 +1,9 @@
+# MacOS
+.DS_Store
+
+# Vagrant
+.vagrant
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]
diff --git a/Vagrantfile b/Vagrantfile
new file mode 100644
index 0000000..6070543
--- /dev/null
+++ b/Vagrantfile
@@ -0,0 +1,91 @@
+# -*- mode: ruby -*-
+# vi: set ft=ruby :
+
+# All Vagrant configuration is done below. The "2" in Vagrant.configure
+# configures the configuration version (we support older styles for
+# backwards compatibility). Please don't change it unless you know what
+# you're doing.
+Vagrant.configure("2") do |config|
+  # The most common configuration options are documented and commented below.
+  # For a complete reference, please see the online documentation at
+  # https://docs.vagrantup.com.
+
+  # Every Vagrant development environment requires a box. You can search for
+  # boxes at https://vagrantcloud.com/search.
+  config.vm.box = "hashicorp/bionic64"
+
+  # Disable automatic box update checking. If you disable this, then
+  # boxes will only be checked for updates when the user runs
+  # `vagrant box outdated`. This is not recommended.
+  # config.vm.box_check_update = false
+
+  # Create a forwarded port mapping which allows access to a specific port
+  # within the machine from a port on the host machine. In the example below,
+  # accessing "localhost:8080" will access port 80 on the guest machine.
+  # NOTE: This will enable public access to the opened port
+  config.vm.network "forwarded_port", guest: 8888, host: 8888
+
+  # Create a forwarded port mapping which allows access to a specific port
+  # within the machine from a port on the host machine and only allow access
+  # via 127.0.0.1 to disable public access
+  # config.vm.network "forwarded_port", guest: 80, host: 8080, host_ip: "127.0.0.1"
+
+  # Create a private network, which allows host-only access to the machine
+  # using a specific IP.
+  # config.vm.network "private_network", ip: "192.168.33.10"
+
+  # Create a public network, which generally matched to bridged network.
+  # Bridged networks make the machine appear as another physical device on
+  # your network.
+  # config.vm.network "public_network"
+
+  # Share an additional folder to the guest VM. The first argument is
+  # the path on the host to the actual folder. The second argument is
+  # the path on the guest to mount the folder. And the optional third
+  # argument is a set of non-required options.
+  # config.vm.synced_folder "../data", "/vagrant_data"
+
+  # Provider-specific configuration so you can fine-tune various
+  # backing providers for Vagrant. These expose provider-specific options.
+  # Example for VirtualBox:
+  #
+  # config.vm.provider "virtualbox" do |vb|
+  #   # Display the VirtualBox GUI when booting the machine
+  #   vb.gui = true
+  #
+  #   # Customize the amount of memory on the VM:
+  #   vb.memory = "1024"
+  # end
+  #
+  # View the documentation for the provider you are using for more
+  # information on available options.
+
+  # Enable provisioning with a shell script. Additional provisioners such as
+  # Ansible, Chef, Docker, Puppet and Salt are also available. Please see the
+  # documentation for more information about their specific syntax and use.
+  config.vm.provision "shell", name: "Install Mambaforge", privileged: false, reset: true, inline: <<-SHELL
+    MAMBA_FORGE_FILE=Mambaforge-$(uname)-$(uname -m).sh
+    if ! [ -d ~/mambaforge ]; then
+      if ! [ -f $MAMBA_FORGE_FILE ]; then
+        wget -q https://github.com/conda-forge/miniforge/releases/latest/download/$MAMBA_FORGE_FILE
+      fi
+      bash $MAMBA_FORGE_FILE -b -u
+      rm -f $MAMBA_FORGE_FILE
+
+      mambaforge/bin/conda init --all
+    fi
+  SHELL
+
+  config.vm.provision "shell", name: "Install OS Packages", inline: <<-SHELL
+    ### Add OpenJDK 8
+    apt-get update
+    apt-get --yes install openjdk-8-jre-headless
+  SHELL
+
+  config.vm.provision "shell", name: "Create Development Environment", privileged: false, inline: <<-SHELL
+    ### Create the DarkNet Environment
+    source mambaforge/etc/profile.d/conda.sh
+    mamba env update --name darknet-cpu -f /vagrant/environment.yml
+    echo 'conda activate darknet-cpu' >> ~/.bashrc
+  SHELL
+end
diff --git a/environment.yml b/environment.yml
index cd34fd5..1176b58 100644
--- a/environment.yml
+++ b/environment.yml
@@ -1,4 +1,3 @@
-
 name: darknet.py-dev
 channels:
   - zeroae
@@ -9,6 +8,8 @@ dependencies:
   - pip
   - pip:
     - -e .
+    - multi-model-server
+    - sagemaker-inference
 
   # Setup Requirements (setup.py:setup_requirements)
   - compilers
@@ -21,7 +22,7 @@ dependencies:
   # Install Requirements (setup.py:requirements)
   - click >=7.0
   - click-plugins
-  - darknet
+  - darknet-cpu
   - entrypoints
   - fsspec <=0.7.5
   - numpy
@@ -30,6 +31,12 @@ dependencies:
   # Zoo Optional Requirements
   - intake
 
+  # MMS Requirements
+  - enum-compat
+  - future
+  - retrying
+  - scipy
+
   # Test Requirements (setup.py:test_requirements)
   - pytest >=3
   - pytest-cov
diff --git a/setup.py b/setup.py
index 254725d..ddf9f67 100755
--- a/setup.py
+++ b/setup.py
@@ -47,6 +47,14 @@
     # fmt: on
 ]
 
+mms_requirements = [
+    # fmt: off
+    "future",
+    "multi-model-server",
+    "retrying",
+    "sagemaker-inference",
+    # fmt: on
+]
 zoo_requirements = [
     # fmt: off
     "intake",
@@ -130,7 +138,7 @@
     long_description_content_type="text/x-rst",
     include_package_data=True,
     keywords="py darknet",
-    name="darknet-py",
+    name="darknet.py",
     package_dir={"": "src"},
     packages=find_namespace_packages(where="./src"),
     setup_requires=setup_requirements,
@@ -141,6 +149,7 @@
         "test": test_requirements,
         "doc": doc_requirements,
         "zoo": zoo_requirements,
+        "mms": mms_requirements,
         # fmt: on
     },
     url="https://github.com/zeroae/darknet.py",
diff --git a/src/darknet/py/__init__.py b/src/darknet/py/__init__.py
index a810fc5..80945b2 100644
--- a/src/darknet/py/__init__.py
+++ b/src/darknet/py/__init__.py
@@ -1,6 +1,7 @@
 """Top-level package for DarkNet OpenSource Neural Networks in Python."""
 from ._version import version as __version__  # noqa: F401
+from .network import Network
 from .classifier import Classifier, ImageClassifier
 from .detector import ImageDetector
 
-__all__ = ["Classifier", "ImageClassifier", "ImageDetector"]
+__all__ = ["Network", "Classifier", "ImageClassifier", "ImageDetector"]
diff --git a/src/darknet/sagemaker/__init__.py b/src/darknet/sagemaker/__init__.py
new file mode 100644
index 0000000..383b92b
--- /dev/null
+++ b/src/darknet/sagemaker/__init__.py
@@ -0,0 +1,4 @@
+from .default_inference_handler import DefaultDarknetInferenceHandler, Network
+from ..py.util import image_to_3darray
+
+__all__ = ["DefaultDarknetInferenceHandler", "Network", "image_to_3darray"]
diff --git a/src/darknet/sagemaker/__main__.py b/src/darknet/sagemaker/__main__.py
new file mode 100644
index 0000000..78a4a68
--- /dev/null
+++ b/src/darknet/sagemaker/__main__.py
@@ -0,0 +1,29 @@
+from retrying import retry
+from subprocess import CalledProcessError
+from sagemaker_inference import model_server
+
+from .classfier import handler_service as classifier_service
+from .detector import handler_service as detector_service
+
+
+def _retry_if_error(exception):
+    return isinstance(exception, CalledProcessError or OSError)
+
+
+@retry(stop_max_delay=1000 * 50,
+       retry_on_exception=_retry_if_error)
+def _start_mms():
+    # by default the number of workers per model is 1, but we can configure it through the
+    # environment variable below if desired.
+    # os.environ['SAGEMAKER_MODEL_SERVER_WORKERS'] = '2'
+    # TODO: Start Classifier *or* Detector Service
+    model_server.start_model_server(
+        handler_service=detector_service.__name__
+    )
+
+
+def main():
+    _start_mms()
+
+
+main()
diff --git a/src/darknet/sagemaker/classifier/__init__.py b/src/darknet/sagemaker/classifier/__init__.py
new file mode 100644
index 0000000..ddee0ce
--- /dev/null
+++ b/src/darknet/sagemaker/classifier/__init__.py
@@ -0,0 +1,3 @@
+from .handler_service import HandlerService
+
+__all__ = ["HandlerService"]
diff --git a/src/darknet/sagemaker/classifier/__main__.py b/src/darknet/sagemaker/classifier/__main__.py
new file mode 100644
index 0000000..14dfa1a
--- /dev/null
+++ b/src/darknet/sagemaker/classifier/__main__.py
@@ -0,0 +1,28 @@
+from retrying import retry
+from subprocess import CalledProcessError
+from sagemaker_inference import model_server
+
+from . import handler_service as classifier_service
+
+
+def _retry_if_error(exception):
+    return isinstance(exception, CalledProcessError or OSError)
+
+
+@retry(stop_max_delay=1000 * 50,
+       retry_on_exception=_retry_if_error)
+def _start_mms():
+    # by default the number of workers per model is 1, but we can configure it through the
+    # environment variable below if desired.
+    # os.environ['SAGEMAKER_MODEL_SERVER_WORKERS'] = '2'
+    # TODO: Start Classifier *or* Detector Service
+    model_server.start_model_server(
+        handler_service=classifier_service.__name__
+    )
+
+
+def main():
+    _start_mms()
+
+
+main()
diff --git a/src/darknet/sagemaker/classifier/default_inference_handler.py b/src/darknet/sagemaker/classifier/default_inference_handler.py
new file mode 100644
index 0000000..0ff7fef
--- /dev/null
+++ b/src/darknet/sagemaker/classifier/default_inference_handler.py
@@ -0,0 +1,38 @@
+import PIL.Image as Image
+
+from typing import Tuple, List
+from sagemaker_inference import content_types, decoder, encoder, errors
+
+from .. import DefaultDarknetInferenceHandler, image_to_3darray
+
+
+class DefaultDarknetClassifierInferenceHandler(DefaultDarknetInferenceHandler):
+
+    def default_predict_fn(self, data, model: Tuple[Network, List[str]]):
+        """A default predict_fn for DarkNet. Calls a model on data deserialized in input_fn.
+        Args:
+            data: input data (PIL.Image) for prediction deserialized by input_fn
+            model: Darknet model loaded in memory by model_fn
+
+        Returns: a prediction
+        """
+        network, labels = model
+        if isinstance(data, Image.Image):
+            image, _ = image_to_3darray(data, network.shape)
+            probabilities = network.predict_image(image)
+        else:
+            probabilities = network.predict(data)
+
+        return zip(labels, probabilities)
+
+    def default_output_fn(self, prediction, accept):
+        """A default output_fn for PyTorch. Serializes predictions from predict_fn to JSON, CSV or NPY format.
+
+        Args:
+            prediction: a prediction result from predict_fn
+            accept: type which the output data needs to be serialized
+
+        Returns: output data serialized
+        """
+        prediction = sorted(prediction, key=lambda x: x[1], reverse=True)[0:5]
+        return encoder.encode(list(prediction), accept)
diff --git a/src/darknet/sagemaker/classifier/handler_service.py b/src/darknet/sagemaker/classifier/handler_service.py
new file mode 100644
index 0000000..3d105f3
--- /dev/null
+++ b/src/darknet/sagemaker/classifier/handler_service.py
@@ -0,0 +1,19 @@
+from sagemaker_inference.default_handler_service import DefaultHandlerService
+from sagemaker_inference.transformer import Transformer
+
+from .default_inference_handler import DefaultDarknetClassifierInferenceHandler
+
+
+class HandlerService(DefaultHandlerService):
+    """Handler service that is executed by the model server.
+    Determines specific default inference handlers to use based on the type MXNet model being used.
+    This class extends ``DefaultHandlerService``, which define the following:
+        - The ``handle`` method is invoked for all incoming inference requests to the model server.
+        - The ``initialize`` method is invoked at model server start up.
+    Based on: https://github.com/awslabs/mxnet-model-server/blob/master/docs/custom_service.md
+    """
+    def __init__(self):
+        self._initialized = False
+
+        transformer = Transformer(default_inference_handler=DefaultDarknetClassifierInferenceHandler())
+        super(HandlerService, self).__init__(transformer=transformer)
diff --git a/src/darknet/sagemaker/default_inference_handler.py b/src/darknet/sagemaker/default_inference_handler.py
new file mode 100644
index 0000000..e9f0134
--- /dev/null
+++ b/src/darknet/sagemaker/default_inference_handler.py
@@ -0,0 +1,43 @@
+import io
+import numpy as np
+import PIL.Image as Image
+
+from abc import ABC
+from glob import glob
+from typing import Tuple, List, Union
+
+from sagemaker_inference.decoder import decode
+from sagemaker_inference.default_inference_handler import DefaultInferenceHandler
+
+from ..py import Network
+
+
+class DefaultDarknetInferenceHandler(DefaultInferenceHandler, ABC):
+    def default_model_fn(self, model_dir) -> Tuple[Network, List[str]]:
+        """
+        Loads a model.
+        For PyTorch, a default function to load a model cannot be provided.
+        Returns: A DarkNet Detector.
+        """
+        labels_file = glob(f"{model_dir}/*.labels")[0]
+        with open(labels_file) as f:
+            labels = [line.rstrip() for line in f.readlines()]
+
+        cfg_file = glob(f"{model_dir}/*.cfg")[0]
+        weights_file = glob(f"{model_dir}/*.weights")[0]
+
+        return Network(cfg_file, weights_file, batch_size=1), labels
+
+    def default_input_fn(self, input_data, content_type) -> Union[Image.Image, np.array]:
+        """A default input_fn that can handle PIL Image Types
+
+        Args:
+            input_data: the request payload serialized in the content_type format
+            content_type: the request content_type
+
+        Returns: a PIL Image ready for ImageClassifier
+        """
+        if content_type.startswith("image/"):
+            image = Image.open(io.BytesIO(input_data))
+            return image
+        return decode(input_data, content_type)
diff --git a/src/darknet/sagemaker/detector/__init__.py b/src/darknet/sagemaker/detector/__init__.py
new file mode 100644
index 0000000..ddee0ce
--- /dev/null
+++ b/src/darknet/sagemaker/detector/__init__.py
@@ -0,0 +1,3 @@
+from .handler_service import HandlerService
+
+__all__ = ["HandlerService"]
diff --git a/src/darknet/sagemaker/detector/__main__.py b/src/darknet/sagemaker/detector/__main__.py
new file mode 100644
index 0000000..3b91989
--- /dev/null
+++ b/src/darknet/sagemaker/detector/__main__.py
@@ -0,0 +1,27 @@
+from retrying import retry
+from subprocess import CalledProcessError
+from sagemaker_inference import model_server
+
+from . import handler_service
+
+
+def _retry_if_error(exception):
+    return isinstance(exception, CalledProcessError or OSError)
+
+
+@retry(stop_max_delay=1000 * 50,
+       retry_on_exception=_retry_if_error)
+def _start_mms():
+    # by default the number of workers per model is 1, but we can configure it through the
+    # environment variable below if desired.
+    # os.environ['SAGEMAKER_MODEL_SERVER_WORKERS'] = '2'
+    model_server.start_model_server(
+        handler_service=handler_service.__name__
+    )
+
+
+def main():
+    _start_mms()
+
+
+main()
diff --git a/src/darknet/sagemaker/detector/default_inference_handler.py b/src/darknet/sagemaker/detector/default_inference_handler.py
new file mode 100644
index 0000000..38eab54
--- /dev/null
+++ b/src/darknet/sagemaker/detector/default_inference_handler.py
@@ -0,0 +1,42 @@
+import PIL.Image as Image
+
+from typing import Tuple, List
+from sagemaker_inference import encoder, errors
+
+from .. import DefaultDarknetInferenceHandler, Network, image_to_3darray
+
+
+class DefaultDarknetDetectorInferenceHandler(DefaultDarknetInferenceHandler):
+    def default_predict_fn(self, data, model: Tuple[Network, List[str]]):
+        """A default predict_fn for DarkNet. Calls a model on data deserialized in input_fn.
+        Args:
+            data: input data (PIL.Image) for prediction deserialized by input_fn
+            model: Darknet model loaded in memory by model_fn
+
+        Returns: detected labels
+        """
+        network, labels = model
+        if not isinstance(data, Image.Image):
+            raise TypeError("Input data is not an Image.")
+
+        image, frame_size = image_to_3darray(data, network.shape)
+        _ = network.predict_image(image)
+        detections = network.detect(frame_size=frame_size)
+
+        return (
+            detections
+            if labels is None
+            else [(labels[label_idx], prob, bbox) for label_idx, prob, bbox in detections]
+        )
+
+    def default_output_fn(self, prediction, accept):
+        """A default output_fn for PyTorch. Serializes predictions from predict_fn to JSON, CSV or NPY format.
+
+        Args:
+            prediction: a prediction result from predict_fn
+            accept: type which the output data needs to be serialized
+
+        Returns: output data serialized (Return Sagemaker format?)
+        """
+        prediction = sorted(prediction, key=lambda x: x[1], reverse=True)[0:5]
+        return encoder.encode(list(prediction), accept)
diff --git a/src/darknet/sagemaker/detector/handler_service.py b/src/darknet/sagemaker/detector/handler_service.py
new file mode 100644
index 0000000..b87db17
--- /dev/null
+++ b/src/darknet/sagemaker/detector/handler_service.py
@@ -0,0 +1,19 @@
+from sagemaker_inference.default_handler_service import DefaultHandlerService
+from sagemaker_inference.transformer import Transformer
+
+from .default_inference_handler import DefaultDarknetDetectorInferenceHandler
+
+
+class HandlerService(DefaultHandlerService):
+    """Handler service that is executed by the model server.
+    Determines specific default inference handlers to use based on the type MXNet model being used.
+    This class extends ``DefaultHandlerService``, which define the following:
+        - The ``handle`` method is invoked for all incoming inference requests to the model server.
+        - The ``initialize`` method is invoked at model server start up.
+    Based on: https://github.com/awslabs/mxnet-model-server/blob/master/docs/custom_service.md
+    """
+    def __init__(self):
+        self._initialized = False
+
+        transformer = Transformer(default_inference_handler=DefaultDarknetDetectorInferenceHandler())
+        super(HandlerService, self).__init__(transformer=transformer)

From 4bf2da316255b84ca44f659ffc05c09e340089a3 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrick=20Sodr=C3=A9?= <psodre@gmail.com>
Date: Tue, 2 Nov 2021 12:00:37 -0400
Subject: [PATCH 02/16] Fix a few typos

---
 src/darknet/sagemaker/__main__.py                             | 2 +-
 src/darknet/sagemaker/classifier/default_inference_handler.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/darknet/sagemaker/__main__.py b/src/darknet/sagemaker/__main__.py
index 78a4a68..cae3e8b 100644
--- a/src/darknet/sagemaker/__main__.py
+++ b/src/darknet/sagemaker/__main__.py
@@ -2,7 +2,7 @@
 from subprocess import CalledProcessError
 from sagemaker_inference import model_server
 
-from .classfier import handler_service as classifier_service
+from .classifier import handler_service as classifier_service
 from .detector import handler_service as detector_service
 
 
diff --git a/src/darknet/sagemaker/classifier/default_inference_handler.py b/src/darknet/sagemaker/classifier/default_inference_handler.py
index 0ff7fef..125e0c0 100644
--- a/src/darknet/sagemaker/classifier/default_inference_handler.py
+++ b/src/darknet/sagemaker/classifier/default_inference_handler.py
@@ -3,7 +3,7 @@
 from typing import Tuple, List
 from sagemaker_inference import content_types, decoder, encoder, errors
 
-from .. import DefaultDarknetInferenceHandler, image_to_3darray
+from .. import DefaultDarknetInferenceHandler, image_to_3darray, Network
 
 
 class DefaultDarknetClassifierInferenceHandler(DefaultDarknetInferenceHandler):

From df8570842e6644f79febf605e405cac7ecff9dc5 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrick=20Sodr=C3=A9?= <psodre@gmail.com>
Date: Wed, 3 Nov 2021 00:38:49 -0400
Subject: [PATCH 03/16] Convert prediction output format to conform to AWS
 Rekognition.

Ref: https://docs.aws.amazon.com/rekognition/latest/dg/API_DetectLabels.html
---
 .../classifier/default_inference_handler.py   | 23 +++-----
 .../sagemaker/default_inference_handler.py    | 12 +++++
 .../detector/default_inference_handler.py     | 54 ++++++++++++-------
 3 files changed, 56 insertions(+), 33 deletions(-)

diff --git a/src/darknet/sagemaker/classifier/default_inference_handler.py b/src/darknet/sagemaker/classifier/default_inference_handler.py
index 125e0c0..fde3096 100644
--- a/src/darknet/sagemaker/classifier/default_inference_handler.py
+++ b/src/darknet/sagemaker/classifier/default_inference_handler.py
@@ -1,13 +1,11 @@
 import PIL.Image as Image
 
 from typing import Tuple, List
-from sagemaker_inference import content_types, decoder, encoder, errors
 
 from .. import DefaultDarknetInferenceHandler, image_to_3darray, Network
 
 
 class DefaultDarknetClassifierInferenceHandler(DefaultDarknetInferenceHandler):
-
     def default_predict_fn(self, data, model: Tuple[Network, List[str]]):
         """A default predict_fn for DarkNet. Calls a model on data deserialized in input_fn.
         Args:
@@ -17,22 +15,17 @@ def default_predict_fn(self, data, model: Tuple[Network, List[str]]):
         Returns: a prediction
         """
         network, labels = model
+        max_labels = 5
+        min_confidence = 55
+
         if isinstance(data, Image.Image):
             image, _ = image_to_3darray(data, network.shape)
             probabilities = network.predict_image(image)
         else:
             probabilities = network.predict(data)
 
-        return zip(labels, probabilities)
-
-    def default_output_fn(self, prediction, accept):
-        """A default output_fn for PyTorch. Serializes predictions from predict_fn to JSON, CSV or NPY format.
-
-        Args:
-            prediction: a prediction result from predict_fn
-            accept: type which the output data needs to be serialized
-
-        Returns: output data serialized
-        """
-        prediction = sorted(prediction, key=lambda x: x[1], reverse=True)[0:5]
-        return encoder.encode(list(prediction), accept)
+        rv = [{
+            "Name": label,
+            "Confidence": prob*100,
+        } for label, prob in sorted(zip(labels, probabilities), key=lambda x: x[1], reverse=True)]
+        return {"Labels": rv[0:max_labels] if max_labels else rv}
diff --git a/src/darknet/sagemaker/default_inference_handler.py b/src/darknet/sagemaker/default_inference_handler.py
index e9f0134..c5632b1 100644
--- a/src/darknet/sagemaker/default_inference_handler.py
+++ b/src/darknet/sagemaker/default_inference_handler.py
@@ -6,6 +6,7 @@
 from glob import glob
 from typing import Tuple, List, Union
 
+from sagemaker_inference.encoder import encode
 from sagemaker_inference.decoder import decode
 from sagemaker_inference.default_inference_handler import DefaultInferenceHandler
 
@@ -41,3 +42,14 @@ def default_input_fn(self, input_data, content_type) -> Union[Image.Image, np.ar
             image = Image.open(io.BytesIO(input_data))
             return image
         return decode(input_data, content_type)
+
+    def default_output_fn(self, prediction, accept):
+        """A default output_fn for PyTorch. Serializes predictions from predict_fn to JSON, CSV or NPY format.
+
+        Args:
+            prediction: a prediction result from predict_fn
+            accept: type which the output data needs to be serialized
+
+        Returns: output data serialized (Return Sagemaker format?)
+        """
+        return encode(prediction, accept)
diff --git a/src/darknet/sagemaker/detector/default_inference_handler.py b/src/darknet/sagemaker/detector/default_inference_handler.py
index 38eab54..b7a7ef8 100644
--- a/src/darknet/sagemaker/detector/default_inference_handler.py
+++ b/src/darknet/sagemaker/detector/default_inference_handler.py
@@ -1,7 +1,9 @@
+from itertools import groupby
+
 import PIL.Image as Image
 
 from typing import Tuple, List
-from sagemaker_inference import encoder, errors
+from sagemaker_inference import errors
 
 from .. import DefaultDarknetInferenceHandler, Network, image_to_3darray
 
@@ -16,27 +18,43 @@ def default_predict_fn(self, data, model: Tuple[Network, List[str]]):
         Returns: detected labels
         """
         network, labels = model
+        max_labels = None
+        min_confidence = 55
+
         if not isinstance(data, Image.Image):
             raise TypeError("Input data is not an Image.")
 
         image, frame_size = image_to_3darray(data, network.shape)
         _ = network.predict_image(image)
-        detections = network.detect(frame_size=frame_size)
-
-        return (
-            detections
-            if labels is None
-            else [(labels[label_idx], prob, bbox) for label_idx, prob, bbox in detections]
+        detections = network.detect(
+            frame_size=frame_size,
+            threshold=min_confidence/100.0,
+            hierarchical_threshold=min_confidence/100,
         )
+        detections = sorted(detections, key=lambda x: x[0])
+
+        def bbox_to_sm_map(x_0, y_0, w, h):
+            return {
+                "Width": w,
+                "Height": h,
+                "Left": x_0 - w/2,
+                "Top": y_0 + h/2
+            }
+
+        rv = []
+        for label_idx, instances in groupby(detections, key=lambda x: x[0]):
+            instances = [{
+                    "Confidence": prob*100,
+                    "BoundingBox": bbox_to_sm_map(*bbox)
+                } for _, prob, bbox in sorted(instances, key=lambda x: x[1], reverse=True)
+            ]
+            detection = {
+                "Name": labels[label_idx],
+                "Confidence": instances[0]["Confidence"],
+                "Instances": instances,
+                "Parents": []
+            }
+            detection["Confidence"] = detection["Instances"][0]["Confidence"]
+            rv.append(detection)
+        return {"Labels": rv[0:max_labels] if max_labels else rv}
 
-    def default_output_fn(self, prediction, accept):
-        """A default output_fn for PyTorch. Serializes predictions from predict_fn to JSON, CSV or NPY format.
-
-        Args:
-            prediction: a prediction result from predict_fn
-            accept: type which the output data needs to be serialized
-
-        Returns: output data serialized (Return Sagemaker format?)
-        """
-        prediction = sorted(prediction, key=lambda x: x[1], reverse=True)[0:5]
-        return encoder.encode(list(prediction), accept)

From edce6ece302b471ce21d2d3705afdc5cc6801c05 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrick=20Sodr=C3=A9?= <psodre@gmail.com>
Date: Wed, 3 Nov 2021 00:39:40 -0400
Subject: [PATCH 04/16] Increase VagrantBox memory to 2GB.

---
 Vagrantfile | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/Vagrantfile b/Vagrantfile
index 6070543..9e13fe7 100644
--- a/Vagrantfile
+++ b/Vagrantfile
@@ -59,6 +59,9 @@ Vagrant.configure("2") do |config|
   #
   # View the documentation for the provider you are using for more
   # information on available options.
+  config.vm.provider "vmware_desktop" do |v|
+    v.vmx["memsize"] = "2048"
+  end
 
   # Enable provisioning with a shell script. Additional provisioners such as
   # Ansible, Chef, Docker, Puppet and Salt are also available. Please see the

From f87d8a93c54726a50040f2adbfcaa78bd5ebc3c9 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrick=20Sodr=C3=A9?= <psodre@gmail.com>
Date: Wed, 3 Nov 2021 01:47:28 -0400
Subject: [PATCH 05/16] Refactor code

---
 .../classifier/default_inference_handler.py       | 14 +++++++++-----
 .../sagemaker/default_inference_handler.py        |  9 +++++++--
 .../detector/default_inference_handler.py         | 15 +++++++++------
 3 files changed, 25 insertions(+), 13 deletions(-)

diff --git a/src/darknet/sagemaker/classifier/default_inference_handler.py b/src/darknet/sagemaker/classifier/default_inference_handler.py
index fde3096..43d5380 100644
--- a/src/darknet/sagemaker/classifier/default_inference_handler.py
+++ b/src/darknet/sagemaker/classifier/default_inference_handler.py
@@ -2,6 +2,8 @@
 
 from typing import Tuple, List
 
+from sagemaker_inference.errors import UnsupportedFormatError
+
 from .. import DefaultDarknetInferenceHandler, image_to_3darray, Network
 
 
@@ -15,14 +17,16 @@ def default_predict_fn(self, data, model: Tuple[Network, List[str]]):
         Returns: a prediction
         """
         network, labels = model
-        max_labels = 5
-        min_confidence = 55
+        max_labels = data.get("MaxLabels", 5)
+        min_confidence = data.get("MinConfidence", 55)
 
-        if isinstance(data, Image.Image):
-            image, _ = image_to_3darray(data, network.shape)
+        if "NDArray" in data:
+            probabilities = network.predict(data["NDArray"])
+        elif "Image" in data:
+            image, _ = image_to_3darray(data["Image"], network.shape)
             probabilities = network.predict_image(image)
         else:
-            probabilities = network.predict(data)
+            raise UnsupportedFormatError("Expected an NDArray or an Image")
 
         rv = [{
             "Name": label,
diff --git a/src/darknet/sagemaker/default_inference_handler.py b/src/darknet/sagemaker/default_inference_handler.py
index c5632b1..60ecb99 100644
--- a/src/darknet/sagemaker/default_inference_handler.py
+++ b/src/darknet/sagemaker/default_inference_handler.py
@@ -1,8 +1,12 @@
 import io
+import json
+
+import base64
 import numpy as np
 import PIL.Image as Image
 
 from abc import ABC
+from base64 import b64decode
 from glob import glob
 from typing import Tuple, List, Union
 
@@ -40,8 +44,9 @@ def default_input_fn(self, input_data, content_type) -> Union[Image.Image, np.ar
         """
         if content_type.startswith("image/"):
             image = Image.open(io.BytesIO(input_data))
-            return image
-        return decode(input_data, content_type)
+            return {"Image": image}
+        else:
+            return {"NDArray": decode(input_data, content_type)}
 
     def default_output_fn(self, prediction, accept):
         """A default output_fn for PyTorch. Serializes predictions from predict_fn to JSON, CSV or NPY format.
diff --git a/src/darknet/sagemaker/detector/default_inference_handler.py b/src/darknet/sagemaker/detector/default_inference_handler.py
index b7a7ef8..1e56706 100644
--- a/src/darknet/sagemaker/detector/default_inference_handler.py
+++ b/src/darknet/sagemaker/detector/default_inference_handler.py
@@ -3,7 +3,7 @@
 import PIL.Image as Image
 
 from typing import Tuple, List
-from sagemaker_inference import errors
+from sagemaker_inference.errors import UnsupportedFormatError
 
 from .. import DefaultDarknetInferenceHandler, Network, image_to_3darray
 
@@ -17,15 +17,18 @@ def default_predict_fn(self, data, model: Tuple[Network, List[str]]):
 
         Returns: detected labels
         """
+        if "Image" not in data:
+            raise UnsupportedFormatError("Detector model expects an Image.")
+
         network, labels = model
-        max_labels = None
-        min_confidence = 55
 
-        if not isinstance(data, Image.Image):
-            raise TypeError("Input data is not an Image.")
+        max_labels = data.get("MaxLabels", None)
+        min_confidence = data.get("MinConfidence", 55)
 
-        image, frame_size = image_to_3darray(data, network.shape)
+        image = data["Image"]
+        image, frame_size = image_to_3darray(image, network.shape)
         _ = network.predict_image(image)
+
         detections = network.detect(
             frame_size=frame_size,
             threshold=min_confidence/100.0,

From b1af2cd6b628f19e7ba7ef6c2754c76fe240a67c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrick=20Sodr=C3=A9?= <psodre@gmail.com>
Date: Wed, 3 Nov 2021 02:00:45 -0400
Subject: [PATCH 06/16] Update actions/setup-python@v2.2.2

---
 .github/workflows/pypa-conda.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/pypa-conda.yml b/.github/workflows/pypa-conda.yml
index 38c4bb6..dc99ecc 100644
--- a/.github/workflows/pypa-conda.yml
+++ b/.github/workflows/pypa-conda.yml
@@ -28,7 +28,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     steps:
       - uses: actions/checkout@v1
-      - uses: actions/setup-python@v1.1.1
+      - uses: actions/setup-python@v2.2.2
         with:
           python-version: ${{ matrix.python-version }}
       - uses: actions/cache@v1

From 620690f834d0560acf3b2746409ec049e9e3fe86 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrick=20Sodr=C3=A9?= <psodre@gmail.com>
Date: Wed, 3 Nov 2021 06:02:14 +0000
Subject: [PATCH 07/16] Make it black

---
 src/darknet/sagemaker/__main__.py             |  7 ++-----
 src/darknet/sagemaker/classifier/__main__.py  |  7 ++-----
 .../classifier/default_inference_handler.py   | 11 ++++++----
 .../sagemaker/classifier/handler_service.py   |  5 ++++-
 src/darknet/sagemaker/detector/__main__.py    |  7 ++-----
 .../detector/default_inference_handler.py     | 21 +++++++------------
 .../sagemaker/detector/handler_service.py     |  5 ++++-
 7 files changed, 28 insertions(+), 35 deletions(-)

diff --git a/src/darknet/sagemaker/__main__.py b/src/darknet/sagemaker/__main__.py
index cae3e8b..cb005a5 100644
--- a/src/darknet/sagemaker/__main__.py
+++ b/src/darknet/sagemaker/__main__.py
@@ -10,16 +10,13 @@ def _retry_if_error(exception):
     return isinstance(exception, CalledProcessError or OSError)
 
 
-@retry(stop_max_delay=1000 * 50,
-       retry_on_exception=_retry_if_error)
+@retry(stop_max_delay=1000 * 50, retry_on_exception=_retry_if_error)
 def _start_mms():
     # by default the number of workers per model is 1, but we can configure it through the
     # environment variable below if desired.
     # os.environ['SAGEMAKER_MODEL_SERVER_WORKERS'] = '2'
     # TODO: Start Classifier *or* Detector Service
-    model_server.start_model_server(
-        handler_service=detector_service.__name__
-    )
+    model_server.start_model_server(handler_service=detector_service.__name__)
 
 
 def main():
diff --git a/src/darknet/sagemaker/classifier/__main__.py b/src/darknet/sagemaker/classifier/__main__.py
index 14dfa1a..afb949a 100644
--- a/src/darknet/sagemaker/classifier/__main__.py
+++ b/src/darknet/sagemaker/classifier/__main__.py
@@ -9,16 +9,13 @@ def _retry_if_error(exception):
     return isinstance(exception, CalledProcessError or OSError)
 
 
-@retry(stop_max_delay=1000 * 50,
-       retry_on_exception=_retry_if_error)
+@retry(stop_max_delay=1000 * 50, retry_on_exception=_retry_if_error)
 def _start_mms():
     # by default the number of workers per model is 1, but we can configure it through the
     # environment variable below if desired.
     # os.environ['SAGEMAKER_MODEL_SERVER_WORKERS'] = '2'
     # TODO: Start Classifier *or* Detector Service
-    model_server.start_model_server(
-        handler_service=classifier_service.__name__
-    )
+    model_server.start_model_server(handler_service=classifier_service.__name__)
 
 
 def main():
diff --git a/src/darknet/sagemaker/classifier/default_inference_handler.py b/src/darknet/sagemaker/classifier/default_inference_handler.py
index 43d5380..e03efbd 100644
--- a/src/darknet/sagemaker/classifier/default_inference_handler.py
+++ b/src/darknet/sagemaker/classifier/default_inference_handler.py
@@ -28,8 +28,11 @@ def default_predict_fn(self, data, model: Tuple[Network, List[str]]):
         else:
             raise UnsupportedFormatError("Expected an NDArray or an Image")
 
-        rv = [{
-            "Name": label,
-            "Confidence": prob*100,
-        } for label, prob in sorted(zip(labels, probabilities), key=lambda x: x[1], reverse=True)]
+        rv = [
+            {
+                "Name": label,
+                "Confidence": prob * 100,
+            }
+            for label, prob in sorted(zip(labels, probabilities), key=lambda x: x[1], reverse=True)
+        ]
         return {"Labels": rv[0:max_labels] if max_labels else rv}
diff --git a/src/darknet/sagemaker/classifier/handler_service.py b/src/darknet/sagemaker/classifier/handler_service.py
index 3d105f3..cacbf72 100644
--- a/src/darknet/sagemaker/classifier/handler_service.py
+++ b/src/darknet/sagemaker/classifier/handler_service.py
@@ -12,8 +12,11 @@ class HandlerService(DefaultHandlerService):
         - The ``initialize`` method is invoked at model server start up.
     Based on: https://github.com/awslabs/mxnet-model-server/blob/master/docs/custom_service.md
     """
+
     def __init__(self):
         self._initialized = False
 
-        transformer = Transformer(default_inference_handler=DefaultDarknetClassifierInferenceHandler())
+        transformer = Transformer(
+            default_inference_handler=DefaultDarknetClassifierInferenceHandler()
+        )
         super(HandlerService, self).__init__(transformer=transformer)
diff --git a/src/darknet/sagemaker/detector/__main__.py b/src/darknet/sagemaker/detector/__main__.py
index 3b91989..76e5b2a 100644
--- a/src/darknet/sagemaker/detector/__main__.py
+++ b/src/darknet/sagemaker/detector/__main__.py
@@ -9,15 +9,12 @@ def _retry_if_error(exception):
     return isinstance(exception, CalledProcessError or OSError)
 
 
-@retry(stop_max_delay=1000 * 50,
-       retry_on_exception=_retry_if_error)
+@retry(stop_max_delay=1000 * 50, retry_on_exception=_retry_if_error)
 def _start_mms():
     # by default the number of workers per model is 1, but we can configure it through the
     # environment variable below if desired.
     # os.environ['SAGEMAKER_MODEL_SERVER_WORKERS'] = '2'
-    model_server.start_model_server(
-        handler_service=handler_service.__name__
-    )
+    model_server.start_model_server(handler_service=handler_service.__name__)
 
 
 def main():
diff --git a/src/darknet/sagemaker/detector/default_inference_handler.py b/src/darknet/sagemaker/detector/default_inference_handler.py
index 1e56706..647a714 100644
--- a/src/darknet/sagemaker/detector/default_inference_handler.py
+++ b/src/darknet/sagemaker/detector/default_inference_handler.py
@@ -31,33 +31,26 @@ def default_predict_fn(self, data, model: Tuple[Network, List[str]]):
 
         detections = network.detect(
             frame_size=frame_size,
-            threshold=min_confidence/100.0,
-            hierarchical_threshold=min_confidence/100,
+            threshold=min_confidence / 100.0,
+            hierarchical_threshold=min_confidence / 100,
         )
         detections = sorted(detections, key=lambda x: x[0])
 
         def bbox_to_sm_map(x_0, y_0, w, h):
-            return {
-                "Width": w,
-                "Height": h,
-                "Left": x_0 - w/2,
-                "Top": y_0 + h/2
-            }
+            return {"Width": w, "Height": h, "Left": x_0 - w / 2, "Top": y_0 + h / 2}
 
         rv = []
         for label_idx, instances in groupby(detections, key=lambda x: x[0]):
-            instances = [{
-                    "Confidence": prob*100,
-                    "BoundingBox": bbox_to_sm_map(*bbox)
-                } for _, prob, bbox in sorted(instances, key=lambda x: x[1], reverse=True)
+            instances = [
+                {"Confidence": prob * 100, "BoundingBox": bbox_to_sm_map(*bbox)}
+                for _, prob, bbox in sorted(instances, key=lambda x: x[1], reverse=True)
             ]
             detection = {
                 "Name": labels[label_idx],
                 "Confidence": instances[0]["Confidence"],
                 "Instances": instances,
-                "Parents": []
+                "Parents": [],
             }
             detection["Confidence"] = detection["Instances"][0]["Confidence"]
             rv.append(detection)
         return {"Labels": rv[0:max_labels] if max_labels else rv}
-
diff --git a/src/darknet/sagemaker/detector/handler_service.py b/src/darknet/sagemaker/detector/handler_service.py
index b87db17..41a16bc 100644
--- a/src/darknet/sagemaker/detector/handler_service.py
+++ b/src/darknet/sagemaker/detector/handler_service.py
@@ -12,8 +12,11 @@ class HandlerService(DefaultHandlerService):
         - The ``initialize`` method is invoked at model server start up.
     Based on: https://github.com/awslabs/mxnet-model-server/blob/master/docs/custom_service.md
     """
+
     def __init__(self):
         self._initialized = False
 
-        transformer = Transformer(default_inference_handler=DefaultDarknetDetectorInferenceHandler())
+        transformer = Transformer(
+            default_inference_handler=DefaultDarknetDetectorInferenceHandler()
+        )
         super(HandlerService, self).__init__(transformer=transformer)

From 62d5e634aa9b4e42c6012df6150572a2b28f7fbc Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrick=20Sodr=C3=A9?= <psodre@gmail.com>
Date: Wed, 3 Nov 2021 02:05:56 -0400
Subject: [PATCH 08/16] Fix flake8

---
 src/darknet/sagemaker/__main__.py                             | 2 +-
 src/darknet/sagemaker/classifier/default_inference_handler.py | 4 +---
 src/darknet/sagemaker/default_inference_handler.py            | 3 ---
 src/darknet/sagemaker/detector/default_inference_handler.py   | 2 --
 4 files changed, 2 insertions(+), 9 deletions(-)

diff --git a/src/darknet/sagemaker/__main__.py b/src/darknet/sagemaker/__main__.py
index cb005a5..9ea1b9c 100644
--- a/src/darknet/sagemaker/__main__.py
+++ b/src/darknet/sagemaker/__main__.py
@@ -2,7 +2,7 @@
 from subprocess import CalledProcessError
 from sagemaker_inference import model_server
 
-from .classifier import handler_service as classifier_service
+# TODO: from .classifier import handler_service as classifier_service
 from .detector import handler_service as detector_service
 
 
diff --git a/src/darknet/sagemaker/classifier/default_inference_handler.py b/src/darknet/sagemaker/classifier/default_inference_handler.py
index e03efbd..8b6f7b7 100644
--- a/src/darknet/sagemaker/classifier/default_inference_handler.py
+++ b/src/darknet/sagemaker/classifier/default_inference_handler.py
@@ -1,5 +1,3 @@
-import PIL.Image as Image
-
 from typing import Tuple, List
 
 from sagemaker_inference.errors import UnsupportedFormatError
@@ -18,7 +16,7 @@ def default_predict_fn(self, data, model: Tuple[Network, List[str]]):
         """
         network, labels = model
         max_labels = data.get("MaxLabels", 5)
-        min_confidence = data.get("MinConfidence", 55)
+        # TODO: min_confidence = data.get("MinConfidence", 55)
 
         if "NDArray" in data:
             probabilities = network.predict(data["NDArray"])
diff --git a/src/darknet/sagemaker/default_inference_handler.py b/src/darknet/sagemaker/default_inference_handler.py
index 60ecb99..9a3c93c 100644
--- a/src/darknet/sagemaker/default_inference_handler.py
+++ b/src/darknet/sagemaker/default_inference_handler.py
@@ -1,12 +1,9 @@
 import io
-import json
 
-import base64
 import numpy as np
 import PIL.Image as Image
 
 from abc import ABC
-from base64 import b64decode
 from glob import glob
 from typing import Tuple, List, Union
 
diff --git a/src/darknet/sagemaker/detector/default_inference_handler.py b/src/darknet/sagemaker/detector/default_inference_handler.py
index 647a714..2d1d110 100644
--- a/src/darknet/sagemaker/detector/default_inference_handler.py
+++ b/src/darknet/sagemaker/detector/default_inference_handler.py
@@ -1,7 +1,5 @@
 from itertools import groupby
 
-import PIL.Image as Image
-
 from typing import Tuple, List
 from sagemaker_inference.errors import UnsupportedFormatError
 

From 0121987811a89f20fe4bf0c470ea098eaf310b30 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrick=20Sodr=C3=A9?= <psodre@gmail.com>
Date: Wed, 3 Nov 2021 02:09:24 -0400
Subject: [PATCH 09/16] Update workflow to python 3.7

---
 .github/workflows/pypa-conda.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/pypa-conda.yml b/.github/workflows/pypa-conda.yml
index dc99ecc..cb06b73 100644
--- a/.github/workflows/pypa-conda.yml
+++ b/.github/workflows/pypa-conda.yml
@@ -22,7 +22,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest]
-        python-version: [3.6]
+        python-version: [3.7]
         black-version: [19.10b]
         flake8-version: [3.7.9]
     runs-on: ${{ matrix.os }}

From 2b7c9b45b4574978be4732dbb2501aa48ec9e1b2 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrick=20Sodr=C3=A9?= <psodre@gmail.com>
Date: Wed, 3 Nov 2021 02:14:11 -0400
Subject: [PATCH 10/16] Update GitHub workflow

---
 .github/workflows/pypa-conda.yml | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/pypa-conda.yml b/.github/workflows/pypa-conda.yml
index cb06b73..709405a 100644
--- a/.github/workflows/pypa-conda.yml
+++ b/.github/workflows/pypa-conda.yml
@@ -75,7 +75,7 @@ jobs:
           rm -f *.tar.gz
 
       # Create the bdist wheel file
-      - uses: actions/setup-python@v1.1.1
+      - uses: actions/setup-python@v2.2.2
       - uses: actions/cache@v1
         id: cache
         with:
@@ -152,7 +152,7 @@ jobs:
 
       #
       # Setup the test environment, python + .whl + .whl[test]
-      - uses: actions/setup-python@v1.1.1
+      - uses: actions/setup-python@v2.2.2
         with:
           python-version: ${{ matrix.python-version }}
       - name: Get pip cache
@@ -215,7 +215,7 @@ jobs:
         with:
           activate-environment: ''
           auto-activate-base: true
-          conda-build-version: 3.18
+          conda-build-version: 3.21.4
           condarc-file: .github/condarc.yml
       - run: conda install setuptools_scm conda-verify
       - uses: actions/cache@v1

From 4b90502abc82f65cc4fc1f9de8daf2f31e956452 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrick=20Sodr=C3=A9?= <psodre@gmail.com>
Date: Wed, 3 Nov 2021 02:21:23 -0400
Subject: [PATCH 11/16] Update to setup-miniconda@v2

---
 .github/workflows/pypa-conda.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/pypa-conda.yml b/.github/workflows/pypa-conda.yml
index 709405a..08eb96b 100644
--- a/.github/workflows/pypa-conda.yml
+++ b/.github/workflows/pypa-conda.yml
@@ -211,7 +211,7 @@ jobs:
           tar -xvf *.tar.gz --strip 1
           rm *.tar.gz
 
-      - uses: goanpeca/setup-miniconda@v1
+      - uses: conda-incubator/setup-miniconda@v2
         with:
           activate-environment: ''
           auto-activate-base: true
@@ -338,7 +338,7 @@ jobs:
         with:
           path: /usr/share/miniconda/pkgs
           key: ${{ runner.os }}-conda-ac1.7.2
-      - uses: goanpeca/setup-miniconda@v1
+      - uses: conda-incubator/setup-miniconda@v2
         with:
           activate-environment: ''
           auto-activate-base: true

From d9171df7ceff5155687b796b4e2b93ed2d760349 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrick=20Sodr=C3=A9?= <psodre@gmail.com>
Date: Wed, 3 Nov 2021 02:27:50 -0400
Subject: [PATCH 12/16] Fix the darknet import statement

---
 src/darknet/py/__init__.py                         | 2 +-
 src/darknet/sagemaker/default_inference_handler.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/darknet/py/__init__.py b/src/darknet/py/__init__.py
index 80945b2..1ad2a37 100644
--- a/src/darknet/py/__init__.py
+++ b/src/darknet/py/__init__.py
@@ -4,4 +4,4 @@
 from .classifier import Classifier, ImageClassifier
 from .detector import ImageDetector
 
-__all__ = ["Network", "Classifier", "ImageClassifier", "ImageDetector"]
+__all__ = ["Classifier", "ImageClassifier", "ImageDetector"]
diff --git a/src/darknet/sagemaker/default_inference_handler.py b/src/darknet/sagemaker/default_inference_handler.py
index 9a3c93c..94bb866 100644
--- a/src/darknet/sagemaker/default_inference_handler.py
+++ b/src/darknet/sagemaker/default_inference_handler.py
@@ -11,7 +11,7 @@
 from sagemaker_inference.decoder import decode
 from sagemaker_inference.default_inference_handler import DefaultInferenceHandler
 
-from ..py import Network
+from darknet.py.network import Network
 
 
 class DefaultDarknetInferenceHandler(DefaultInferenceHandler, ABC):

From fc5831b4b3d61127226fdb902e059ba63c316c09 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrick=20Sodr=C3=A9?= <psodre@gmail.com>
Date: Wed, 3 Nov 2021 02:30:32 -0400
Subject: [PATCH 13/16] flake8

---
 src/darknet/py/__init__.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/src/darknet/py/__init__.py b/src/darknet/py/__init__.py
index 1ad2a37..a810fc5 100644
--- a/src/darknet/py/__init__.py
+++ b/src/darknet/py/__init__.py
@@ -1,6 +1,5 @@
 """Top-level package for DarkNet OpenSource Neural Networks in Python."""
 from ._version import version as __version__  # noqa: F401
-from .network import Network
 from .classifier import Classifier, ImageClassifier
 from .detector import ImageDetector
 

From 7d1c00a04a83a324d7d2f8878e7f08d4f6d2f9de Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrick=20Sodr=C3=A9?= <psodre@gmail.com>
Date: Wed, 3 Nov 2021 09:33:48 -0400
Subject: [PATCH 14/16] Try build using mambaforge

---
 .github/workflows/pypa-conda.yml | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/pypa-conda.yml b/.github/workflows/pypa-conda.yml
index 08eb96b..0442a14 100644
--- a/.github/workflows/pypa-conda.yml
+++ b/.github/workflows/pypa-conda.yml
@@ -215,9 +215,12 @@ jobs:
         with:
           activate-environment: ''
           auto-activate-base: true
+          miniforge-variant: Mambaforge
+          use-mamba: true
           conda-build-version: 3.21.4
           condarc-file: .github/condarc.yml
-      - run: conda install setuptools_scm conda-verify
+      - run: |
+          mamba install setuptools_scm conda-verify boa
       - uses: actions/cache@v1
         id: conda-pkgs-cache
         with:
@@ -228,7 +231,7 @@ jobs:
       - name: Run conda build
         run: |
           mkdir conda-bld
-          conda build --output-folder conda-bld .
+          conda mambabuild --output-folder conda-bld .
         env:
           ANACONDA_API_TOKEN: ${{ secrets.ANACONDA_API_TOKEN }}
       - name: Create conda-bld/manifest

From 2f7898d2e1bac875bc18535bcb2ec05c884f2de3 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrick=20Sodr=C3=A9?= <psodre@gmail.com>
Date: Wed, 3 Nov 2021 09:55:49 -0400
Subject: [PATCH 15/16] Remove defaults from channels list

---
 .github/condarc.yml | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/.github/condarc.yml b/.github/condarc.yml
index 6c32d74..85e3c8e 100644
--- a/.github/condarc.yml
+++ b/.github/condarc.yml
@@ -1,6 +1,5 @@
 anaconda_upload: false
 channels:
   - zeroae
-  - defaults
   - conda-forge
-show_channel_urls: true
\ No newline at end of file
+show_channel_urls: true

From 59be2960b060cae54810afb17fb8f52eb16eb975 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrick=20Sodr=C3=A9?= <psodre@gmail.com>
Date: Wed, 3 Nov 2021 10:05:29 -0400
Subject: [PATCH 16/16] Use mambabuild locally

---
 Makefile | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/Makefile b/Makefile
index c0919fa..d49f965 100644
--- a/Makefile
+++ b/Makefile
@@ -93,10 +93,10 @@ wheels: dist  ## downloads wheel dependencies
 	ls -l wheels
 
 dist-conda:  ## builds conda-package
-	conda build --no-anaconda-upload --output-folder conda-bld \
+	conda mambabuild --no-anaconda-upload --output-folder conda-bld \
 	  -c zeroae \
 	  -c conda-forge \
-	  -c anaconda .
+	  .
 
 install: clean ## install the package to the active Python's site-packages
-	python setup.py install
\ No newline at end of file
+	python setup.py install