Fix metaflow and tensorflow/tensorboard examples

comet-ml · Jul 9, 2024 · ed70718 · ed70718
1 parent cf71668
commit ed70718
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Showing 2 changed files with 9 additions and 9 deletions.
diff --git a/integrations/model-training/tensorflow/notebooks/Comet_and_Tensorflow.ipynb b/integrations/model-training/tensorflow/notebooks/Comet_and_Tensorflow.ipynb
@@ -26,7 +26,7 @@
    },
    "outputs": [],
    "source": [
-    "%pip install -U \"comet_ml>=3.44.0\" tensorflow tensorflow-datasets"
+    "%pip install -U \"comet_ml>=3.44.0\" tensorflow \"keras>=3.0.0\" tensorflow-datasets"
    ]
   },
   {
@@ -48,7 +48,7 @@
    "source": [
     "import comet_ml\n",
     "\n",
-    "comet_ml.login(project_name=\"comet-example-tensorboard\")"
+    "comet_ml.login(project_name=\"comet-example-tensorboard-gradient-tape-notebook\")"
    ]
   },
   {
@@ -280,10 +280,10 @@
     "\n",
     "for epoch in range(EPOCHS):\n",
     "    # Reset the metrics at the start of the next epoch\n",
-    "    train_loss.reset_states()\n",
-    "    train_accuracy.reset_states()\n",
-    "    test_loss.reset_states()\n",
-    "    test_accuracy.reset_states()\n",
+    "    train_loss.reset_state()\n",
+    "    train_accuracy.reset_state()\n",
+    "    test_loss.reset_state()\n",
+    "    test_accuracy.reset_state()\n",
     "\n",
     "    for images, labels in train_ds:\n",
     "        train_step(images, labels)\n",
@@ -346,9 +346,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.1"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }
diff --git a/...ns/workflow-orchestration/metaflow/metaflow-model-evaluation/metaflow-model-evaluation.py b/...ns/workflow-orchestration/metaflow/metaflow-model-evaluation/metaflow-model-evaluation.py
@@ -215,7 +215,7 @@ def evaluate_classification_metrics(self):
         )
         accuracy = accuracy_score(labels, torch.argmax(predictions, dim=1))
 
-        self.comet_experiment.log_metrics(clf_metrics)
+        self.comet_experiment.log_metrics({"evaluation_by_class": clf_metrics})
         self.comet_experiment.log_metrics({"accuracy": accuracy})
 
         log_model(self.comet_experiment, model, self.input)