Add new tutorial example to OpenFL interactive API

openfl-tutorials/interactive_api/scikit_learn_linear_regression/README.md

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+# Scikit-learn based Linear Regression Tutorial
+
+### 1. About dataset
+
+Generate 1-dimensional noisy data for linear regression of sinusoid. 
+
+Define the below pamameter in shard_config in the envoy_config.yaml file as the random seed for the dataset generation for a specific Envoy 
+- rank
+
+### 2. About model
+
+Linear Regression Lasso Model based on Scikit-learn.
+
+
+### 3. How to run this tutorial (without TLC and locally as a simulation):
+
+1. Run director:
+
+```sh
+cd director folder
+./start_director.sh
+```
+
+2. Run envoy:
+
+Step 1: Activate virtual environment and install packages
+```
+cd envoy folder
+pip install -r requirements.txt
+```
+Step 2: start the envoy
+```sh
+./start_envoy.sh env_instance_1 envoy_config.yaml
+```
+
+Optional: start second envoy:
+
+- Copy `envoy_folder` to another place and follow the same process as above:
+
+```sh
+./start_envoy.sh env_instance_2 envoy_config_2.yaml
+```
+
+3. Run `scikit_learn_linear_regression.ipynb` jupyter notebook:
+
+```sh
+cd workspace
+jupyter lab scikit_learn_linear_regression.ipynb
+```
+
+4. Visualization
+
+```
+tensorboard --logdir logs/
+```

openfl-tutorials/interactive_api/scikit_learn_linear_regression/director/director_config.yaml

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+settings:
+  listen_host: localhost
+  listen_port: 50050
+  sample_shape: ['1'] # Modify this param if experimenting with `n_features` of shard_descriptor.
+  target_shape: ['1']
+  envoy_health_check_period: 5  # in seconds

openfl-tutorials/interactive_api/scikit_learn_linear_regression/director/start_director.sh

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+#!/bin/bash
+set -e
+
+fx director start --disable-tls -c director_config.yaml

openfl-tutorials/interactive_api/scikit_learn_linear_regression/envoy/envoy_config.yaml

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+params:
+  cuda_devices: []
+
+optional_plugin_components: {}
+
+shard_descriptor:
+  template: linreg_shard_descriptor.LinRegSD
+  params:
+    rank: 1
+    n_samples: 80
+    noise: 0.15
+

openfl-tutorials/interactive_api/scikit_learn_linear_regression/envoy/linreg_shard_descriptor.py

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+# Copyright (C) 2020-2021 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+"""Noisy-Sin Shard Descriptor."""
+
+from typing import List
+
+import numpy as np
+
+from openfl.interface.interactive_api.shard_descriptor import ShardDescriptor
+
+
+class LinRegSD(ShardDescriptor):
+    """Shard descriptor class."""
+
+    def __init__(self, rank: int, n_samples: int = 10, noise: float = 0.15) -> None:
+        """
+        Initialize LinReg Shard Descriptor.
+
+        This Shard Descriptor generate random data. Sample features are
+        floats between pi/3 and 5*pi/3, and targets are calculated
+        calculated as sin(feature) + normal_noise.
+        """
+        np.random.seed(rank)  # Setting seed for reproducibility
+        self.n_samples = max(n_samples, 5)
+        self.interval = 240
+        self.x_start = 60
+        x = np.random.rand(n_samples, 1) * self.interval + self.x_start
+        x *= np.pi / 180
+        y = np.sin(x) + np.random.normal(0, noise, size=(n_samples, 1))
+        self.data = np.concatenate((x, y), axis=1)
+
+    def get_dataset(self, dataset_type: str) -> np.ndarray:
+        """
+        Return a shard dataset by type.
+
+        A simple list with elements (x, y) implemets the Shard Dataset interface.
+        """
+        if dataset_type == 'train':
+            return self.data[:self.n_samples // 2]
+        elif dataset_type == 'val':
+            return self.data[self.n_samples // 2:]
+        else:
+            pass
+
+    @property
+    def sample_shape(self) -> List[str]:
+        """Return the sample shape info."""
+        (*x, _) = self.data[0]
+        return [str(i) for i in np.array(x, ndmin=1).shape]
+
+    @property
+    def target_shape(self) -> List[str]:
+        """Return the target shape info."""
+        (*_, y) = self.data[0]
+        return [str(i) for i in np.array(y, ndmin=1).shape]
+
+    @property
+    def dataset_description(self) -> str:
+        """Return the dataset description."""
+        return 'Allowed dataset types are `train` and `val`'

openfl-tutorials/interactive_api/scikit_learn_linear_regression/envoy/requirements.txt

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+openfl>=1.2.1
+numpy>=1.13.3
+scikit-learn>=0.24.1
+matplotlib>=2.0.0
+mistune>=2.0.3 # not directly required, pinned by Snyk to avoid a vulnerability
+setuptools>=65.5.1 # not directly required, pinned by Snyk to avoid a vulnerability
+wheel>=0.38.0 # not directly required, pinned by Snyk to avoid a vulnerability

openfl-tutorials/interactive_api/scikit_learn_linear_regression/envoy/start_envoy.sh

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+#!/bin/bash
+set -e
+ENVOY_NAME=$1
+ENVOY_CONF=$2
+
+fx envoy start -n "$ENVOY_NAME" --disable-tls --envoy-config-path "$ENVOY_CONF" -dh localhost -dp 50050

openfl-tutorials/interactive_api/scikit_learn_linear_regression/workspace/custom_adapter.py

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+# Copyright (C) 2020-2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+"""Custom model numpy adapter."""
+
+from openfl.plugins.frameworks_adapters.framework_adapter_interface import (
+    FrameworkAdapterPluginInterface,
+)
+
+
+class CustomFrameworkAdapter(FrameworkAdapterPluginInterface):
+    """Framework adapter plugin class."""
+
+    @staticmethod
+    def get_tensor_dict(model, optimizer=None):
+        """Extract tensors from a model."""
+        return {'w': model.weights}
+
+    @staticmethod
+    def set_tensor_dict(model, tensor_dict, optimizer=None, device='cpu'):
+        """Load tensors to a model."""
+        model.weights = tensor_dict['w']

openfl-tutorials/interactive_api/scikit_learn_linear_regression/workspace/requirements.txt

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+absl-py==1.4.0
+aiofiles==22.1.0
+aiosqlite==0.17.0
+anyio==3.6.2
+argon2-cffi==21.3.0
+argon2-cffi-bindings==21.2.0
+arrow==1.2.3
+attrs==23.1.0
+Babel==2.12.1
+backcall==0.2.0
+beautifulsoup4==4.12.2
+bleach==6.0.0
+cached-property==1.5.2
+cachetools==5.3.0
+certifi==2022.12.7
+cffi==1.15.1
+charset-normalizer==3.1.0
+click==8.0.1
+cloudpickle==2.2.1
+colorama==0.4.6
+commonmark==0.9.1
+cryptography==40.0.2
+cycler==0.11.0
+debugpy==1.6.7
+decorator==5.1.1
+defusedxml==0.7.1
+docker==6.0.1
+dynaconf==3.1.7
+entrypoints==0.4
+exceptiongroup==1.1.1
+fastjsonschema==2.16.3
+flatbuffers==2.0.7
+flatten-json==0.1.13
+fonttools==4.38.0
+fqdn==1.5.1
+google-auth==2.17.3
+google-auth-oauthlib==0.4.6
+grpcio==1.34.1
+grpcio-tools==1.34.1
+idna==3.4
+importlib-metadata==6.6.0
+importlib-resources==5.12.0
+iniconfig==2.0.0
+ipykernel==6.16.2
+ipython==7.34.0
+ipython-genutils==0.2.0
+ipywidgets==8.0.6
+isoduration==20.11.0
+jax==0.3.13
+jaxlib==0.3.10
+jedi==0.18.2
+Jinja2==3.1.2
+joblib==1.2.0
+json5==0.9.11
+jsonpointer==2.3
+jsonschema==4.17.3
+jupyter==1.0.0
+jupyter-console==6.6.3
+jupyter-events==0.6.3
+jupyter-server==1.24.0
+jupyter-ydoc==0.2.4
+jupyter_client==7.4.9
+jupyter_core==4.12.0
+jupyter_server_fileid==0.9.0
+jupyter_server_ydoc==0.8.0
+jupyterlab==3.6.3
+jupyterlab-pygments==0.2.2
+jupyterlab-widgets==3.0.7
+jupyterlab_server==2.22.1
+kiwisolver==1.4.4
+Markdown==3.4.3
+markdown-it-py==2.2.0
+MarkupSafe==2.1.2
+matplotlib==3.5.3
+matplotlib-inline==0.1.6
+mdurl==0.1.2
+mistune==2.0.5
+nbclassic==0.5.5
+nbclient==0.7.3
+nbconvert==7.3.1
+nbformat==5.8.0
+nest-asyncio==1.5.6
+notebook==6.5.4
+notebook_shim==0.2.2
+numpy==1.21.6
+oauthlib==3.2.2
+openfl==1.2.1
+opt-einsum==3.3.0
+packaging==23.1
+pandas==1.3.5
+pandocfilters==1.5.0
+parso==0.8.3
+pexpect==4.8.0
+pickleshare==0.7.5
+Pillow==9.5.0
+pip==23.1.1
+pkgutil_resolve_name==1.3.10
+pluggy==1.0.0
+prometheus-client==0.16.0
+prompt-toolkit==3.0.38
+protobuf==3.19.6
+psutil==5.9.5
+ptyprocess==0.7.0
+pyasn1==0.5.0
+pyasn1-modules==0.3.0
+pycparser==2.21
+Pygments==2.15.1
+pyparsing==3.0.9
+pyrsistent==0.19.3
+pytest==7.3.1
+python-dateutil==2.8.2
+python-json-logger==2.0.7
+pytz==2023.3
+PyYAML==6.0
+pyzmq==25.0.2
+qtconsole==5.4.2
+QtPy==2.3.1
+requests==2.28.2
+requests-oauthlib==1.3.1
+rfc3339-validator==0.1.4
+rfc3986-validator==0.1.1
+rich==9.1.0
+rsa==4.9
+scikit-learn==1.0.2
+scipy==1.7.3
+Send2Trash==1.8.0
+setuptools==67.7.1
+six==1.16.0
+sniffio==1.3.0
+soupsieve==2.4.1
+tensorboard==2.11.2
+tensorboard-data-server==0.6.1
+tensorboard-plugin-wit==1.8.1
+tensorboardX==2.6
+terminado==0.17.1
+threadpoolctl==3.1.0
+tinycss2==1.2.1
+tomli==2.0.1
+tornado==6.2
+tqdm==4.65.0
+traitlets==5.9.0
+typing-extensions==3.10.0.2
+uri-template==1.2.0
+urllib3==1.26.15
+wcwidth==0.2.6
+webcolors==1.13
+webencodings==0.5.1
+websocket-client==1.5.1
+Werkzeug==2.2.3
+wheel==0.40.0
+widgetsnbextension==4.0.7
+y-py==0.5.9
+ypy-websocket==0.8.2
+zipp==3.15.0