Refactor helper module

docs/fedn.utils.rst

@@ -33,10 +33,10 @@ fedn.utils.dispatcher module
    :undoc-members:
    :show-inheritance:
 
-fedn.utils.helpers module
+fedn.utils.helpers.helpers module
 -------------------------
 
-.. automodule:: fedn.utils.helpers
+.. automodule:: fedn.utils.helpers.helpers
    :members:
    :undoc-members:
    :show-inheritance:

docs/tutorial.rst

@@ -73,7 +73,7 @@ A *entrypoint.py* example can look like this:
     import fire
     import torch
 
-    from fedn.utils.helpers import get_helper, save_metadata, save_metrics
+    from fedn.utils.helpers.helpers import get_helper, save_metadata, save_metrics
 
     HELPER_MODULE = 'pytorchhelper'
     NUM_CLASSES = 10
@@ -298,7 +298,7 @@ For validations it is a requirement that the output is saved in a valid json for
 
    python entrypoint.py validate in_model_path out_json_path <extra-args>
  
-In the code example we use the helper function :py:meth:`fedn.utils.helpers.save_metrics` to save the validation scores as a json file. 
+In the code example we use the helper function :py:meth:`fedn.utils.helpers.helpers.save_metrics` to save the validation scores as a json file. 
 
 The Dahboard in the FEDn UI will plot any scalar metric in this json file, but you can include any type in the file assuming that it is valid json. These values can then be obtained (by an athorized user) from the MongoDB database or using the :py:mod:`fedn.network.api.client`. 
 

examples/mnist-keras/client/entrypoint

@@ -7,7 +7,7 @@ import fire
 import numpy as np
 import tensorflow as tf
 
-from fedn.utils.helpers import get_helper, save_metadata, save_metrics
+from fedn.utils.helpers.helpers import get_helper, save_metadata, save_metrics
 
 HELPER_MODULE = 'numpyhelper'
 helper = get_helper(HELPER_MODULE)

examples/mnist-pytorch/client/entrypoint

@@ -7,7 +7,7 @@ import docker
 import fire
 import torch
 
-from fedn.utils.helpers import get_helper, save_metadata, save_metrics
+from fedn.utils.helpers.helpers import get_helper, save_metadata, save_metrics
 
 HELPER_MODULE = 'numpyhelper'
 helper = get_helper(HELPER_MODULE)

examples/notebooks/API_Example.ipynb

@@ -56,12 +56,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 7,
    "id": "5107f6f9",
    "metadata": {},
    "outputs": [],
    "source": [
-    "client.set_package('../mnist-pytorch/package.tgz', 'pytorchhelper')\n",
+    "client.set_package('../mnist-pytorch/package.tgz', 'numpyhelper')\n",
     "client.set_initial_model('../mnist-pytorch/seed.npz')\n",
     "seed_model = client.get_initial_model()"
    ]
@@ -76,7 +76,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 8,
    "id": "f0380d35",
    "metadata": {},
    "outputs": [],
@@ -94,7 +94,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 9,
    "id": "4f70d7d9",
    "metadata": {},
    "outputs": [],
@@ -104,7 +104,7 @@
     "                    \"session_id\": \"experiment_fedopt\",\n",
     "                    \"aggregator\": \"fedopt\",\n",
     "                    \"model_id\": seed_model['model_id'],\n",
-    "                    \"rounds\": 10\n",
+    "                    \"rounds\": 1\n",
     "                 }\n",
     "\n",
     "result_fedopt = client.start_session(**session_config_fedopt)"
@@ -133,9 +133,7 @@
     "acc = collections.OrderedDict()\n",
     "for model in models[\"result\"]:\n",
     "    model_id = model[\"model\"]\n",
-    "    #print(model_id)\n",
     "    validations = client.list_validations(modelId=model_id)\n",
-    "    #print(validations.items(),'\\n\\n')\n",
     "\n",
     "    for _ , validation in validations.items(): \n",
     "        metrics = json.loads(validation['data'])\n",
@@ -163,9 +161,7 @@
     "acc = collections.OrderedDict()\n",
     "for model in models[\"result\"]:\n",
     "    model_id = model[\"model\"]\n",
-    "    #print(model_id)\n",
     "    validations = client.list_validations(modelId=model_id)\n",
-    "    #print(validations.items(),'\\n\\n')\n",
     "    for _ , validation in validations.items(): \n",
     "        metrics = json.loads(validation['data'])\n",
     "        try:\n",

fedn/fedn/network/clients/client.py

@@ -27,7 +27,7 @@
 from fedn.network.clients.package import PackageRuntime
 from fedn.network.clients.state import ClientState, ClientStateToString
 from fedn.utils.dispatcher import Dispatcher
-from fedn.utils.helpers import get_helper
+from fedn.utils.helpers.helpers import get_helper
 
 CHUNK_SIZE = 1024 * 1024
 VALID_NAME_REGEX = '^[a-zA-Z0-9_-]*$'

fedn/fedn/network/combiner/aggregators/fedavg.py

@@ -30,8 +30,8 @@ def combine_models(self, helper=None, delete_models=True):
         """Aggregate all model updates in the queue by computing an incremental
         weighted average of model parameters.
 
-        :param helper: An instance of :class: `fedn.utils.helpers.HelperBase`, ML framework specific helper, defaults to None
-        :type helper: class: `fedn.utils.helpers.HelperBase`, optional
+        :param helper: An instance of :class: `fedn.utils.helpers.helpers.HelperBase`, ML framework specific helper, defaults to None
+        :type helper: class: `fedn.utils.helpers.helpers.HelperBase`, optional
         :param time_window: The time window for model aggregation, defaults to 180
         :type time_window: int, optional
         :param max_nr_models: The maximum number of updates aggregated, defaults to 100

fedn/fedn/network/combiner/aggregators/fedopt.py

@@ -42,8 +42,8 @@ def __init__(self, storage, server, modelservice, control):
     def combine_models(self, helper=None, delete_models=True):
         """Compute pseudo gradients usigng model updates in the queue.
 
-        :param helper: An instance of :class: `fedn.utils.helpers.HelperBase`, ML framework specific helper, defaults to None
-        :type helper: class: `fedn.utils.helpers.HelperBase`, optional
+        :param helper: An instance of :class: `fedn.utils.helpers.helpers.HelperBase`, ML framework specific helper, defaults to None
+        :type helper: class: `fedn.utils.helpers.helpers.HelperBase`, optional
         :param time_window: The time window for model aggregation, defaults to 180
         :type time_window: int, optional
         :param max_nr_models: The maximum number of updates aggregated, defaults to 100

fedn/fedn/network/combiner/round.py

@@ -6,7 +6,7 @@
 
 from fedn.common.log_config import logger
 from fedn.network.combiner.aggregators.aggregatorbase import get_aggregator
-from fedn.utils.helpers import get_helper
+from fedn.utils.helpers.helpers import get_helper
 
 
 class ModelUpdateError(Exception):
@@ -60,8 +60,8 @@ def push_round_config(self, round_config):
     def load_model_update(self, helper, model_id):
         """Load model update in its native format.
 
-        :param helper: An instance of :class: `fedn.utils.helpers.HelperBase`, ML framework specific helper, defaults to None
-        :type helper: class: `fedn.utils.helpers.HelperBase`
+        :param helper: An instance of :class: `fedn.utils.helpers.helpers.HelperBase`, ML framework specific helper, defaults to None
+        :type helper: class: `fedn.utils.helpers.helpers.HelperBase`
         :param model_id: The ID of the model update, UUID in str format
         :type model_id: str
         """

fedn/fedn/network/controller/controlbase.py

@@ -3,7 +3,7 @@
 from abc import ABC, abstractmethod
 from time import sleep
 
-import fedn.utils.helpers
+import fedn.utils.helpers.helpers
 from fedn.network.api.network import Network
 from fedn.network.combiner.interfaces import CombinerUnavailableError
 from fedn.network.state import ReducerState
@@ -98,7 +98,7 @@ def get_helper(self):
         :rtype: :class:`fedn.utils.plugins.helperbase.HelperBase`
         """
         helper_type = self.statestore.get_helper()
-        helper = fedn.utils.helpers.get_helper(helper_type)
+        helper = fedn.utils.helpers.helpers.get_helper(helper_type)
         if not helper:
             raise MisconfiguredHelper(
                 "Unsupported helper type {}, please configure compute_package.helper !".format(

fedn/fedn/utils/helpers/__init__.py

@@ -1,3 +1,3 @@
-""" The plugins package is responsible for loading model helper functions supporting different ML frameworks. The :class:`fedn.utils.plugins.helperbase.HelperBase` is
-an abstract class which user can implement their own helper functions to support different ML frameworks. """
+""" The helpers package is responsible for serialization/deserialization and numerics operations 
+for various machine learning frameworks. """
 # flake8: noqa

fedn/fedn/utils/helpers/helpers.py

@@ -10,7 +10,7 @@ def get_helper(helper_module_name):
     :param helper_module_name: The name of the helper plugin module.
     :type helper_module_name: str
     :return: A helper instance.
-    :rtype: class: `fedn.utils.helpers.HelperBase`
+    :rtype: class: `fedn.utils.helpers.helpers.HelperBase`
     """
     helper_plugin = HELPER_PLUGIN_PATH.format(helper_module_name)
     helper = importlib.import_module(helper_plugin)

fedn/fedn/utils/helpers/tests/test_numpyhelper.py

@@ -3,7 +3,8 @@
 
 import numpy as np
 
-from fedn.utils.helpers.plugins.numpyhelper import Helper as NumpyHelper
+from fedn.utils.helpers.helpers.plugins.numpyhelper import \
+    Helper as NumpyHelper
 
 
 class TestNumpyHelper(unittest.TestCase):

fedn/fedn/utils/tests/test_helpers.py

@@ -1,7 +1,7 @@
 import os
 import unittest
 
-from fedn.utils.helpers import get_helper, save_metadata, save_metrics
+from fedn.utils.helpers.helpers import get_helper, save_metadata, save_metrics
 
 
 class TestHelpers(unittest.TestCase):