Merge pull request #224 from mlrun/0.10.x-dev

0.10.x dev
mlrun · Feb 10, 2022 · 21c7f36 · 21c7f36
2 parents 55d2504 + 81c8542
commit 21c7f36
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Showing 6 changed files with 205 additions and 77 deletions.
diff --git a/mask-detection/1-training-and-evaluation.ipynb b/mask-detection/1-training-and-evaluation.ipynb
@@ -443,7 +443,7 @@
     "\n",
     "With just one line of code, it seamlessly provides **automatic logging** (for both MLRun and Tensorboard) and **distributed training** by wrapping the `fit` and `evaluate` methods of `tf.keras.Model`.\n",
     "\n",
-    "In addition, in the `evaluate` method code, we use the `TFKerasModelHandler` class. This class supports loading, saving and logging `tf.keras` models with ease, enabling easy versioning of the model and his results, artifacts and custom objects."
+    "In addition, there is the `TFKerasModelHandler` class that is being returned from `apply_mlrun`. This class supports loading, saving and logging `tf.keras` models with ease, enabling easy versioning of the model and his results, artifacts and custom objects. Pay attention that by default, the model is loaded and logged automatically by `apply_mlrun`."
    ]
   },
   {
@@ -1116,13 +1116,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We will now save our project with the registered functions for using them later in the pipeline:"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/mask-detection/3-automatic-pipeline.ipynb b/mask-detection/3-automatic-pipeline.ipynb
@@ -159,7 +159,7 @@
     "project.set_function(\"hub://open_archive\", name=\"open_archive\")\n",
     "\n",
     "# Import the `onnx_utils` function to optimize the model:\n",
-    "project.set_function(\"hub://onnx_utils:development\", name=\"onnx_utils\")"
+    "project.set_function(\"hub://onnx_utils\", name=\"onnx_utils\")"
    ]
   },
   {
@@ -719,4 +719,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}
diff --git a/mask-detection/pytorch/training-and-evaluation.py b/mask-detection/pytorch/training-and-evaluation.py
@@ -268,7 +268,7 @@ def evaluate(
     # Initialize the loss:
     loss = torch.nn.MSELoss()
 
-    # Evaluate:
+    # Evaluate (the model will be loaded automatically from the provided model path):
     mlrun_torch.evaluate(
         model_path=model_path,
         dataset=evaluation_set,

diff --git a/mask-detection/tf-keras/training-and-evaluation.py b/mask-detection/tf-keras/training-and-evaluation.py
@@ -175,16 +175,8 @@ def evaluate(
         dataset_path=dataset_path, batch_size=batch_size, is_evaluation=True
     )
 
-    # Load the model using MLRun's model handler:
-    model_handler = mlrun_tf_keras.TFKerasModelHandler(
-        model_name="mask_detector", model_path=model_path, context=context
-    )
-    model_handler.load()
-
-    # Apply MLRun's interface for tf.keras:
-    mlrun_tf_keras.apply_mlrun(
-        model=model_handler.model,
-        model_name="mask_detector",
+    # Apply MLRun's interface for tf.keras and load the model:
+    model_handler = mlrun_tf_keras.apply_mlrun(
         model_path=model_path,
         context=context,
     )