Clean the last reference to comet_ml.init

Author: Lothiraldan

catalyst/comet_catalyst_example.py

@@ -1,27 +1,33 @@
-import comet_ml
+# coding: utf-8
+
 import os
+
+import comet_ml
+
 from torch import nn, optim
 from torch.utils.data import DataLoader
+
 from catalyst import dl
+from catalyst.contrib.datasets import MNIST
 from catalyst.data import ToTensor
 from catalyst.loggers.comet import CometLogger
-from catalyst.contrib.datasets import MNIST
 
-comet_ml.init()
+comet_ml.login()
 logger = CometLogger(logging_frequency=10)
 
 model = nn.Sequential(nn.Flatten(), nn.Linear(28 * 28, 10))
 criterion = nn.CrossEntropyLoss()
 optimizer = optim.Adam(model.parameters(), lr=0.02)
 
 
-
 loaders = {
     "train": DataLoader(
-        MNIST(os.getcwd(), train=True, download=True, transform=ToTensor()), batch_size=32
+        MNIST(os.getcwd(), train=True, download=True, transform=ToTensor()),
+        batch_size=32,
     ),
     "valid": DataLoader(
-        MNIST(os.getcwd(), train=False, download=True, transform=ToTensor()), batch_size=32
+        MNIST(os.getcwd(), train=False, download=True, transform=ToTensor()),
+        batch_size=32,
     ),
 }
 
@@ -37,14 +43,16 @@
     loaders=loaders,
     num_epochs=1,
     hparams={
-        'lr': 0.02,
-        'betas': (0.9, 0.999),
-        'eps': 1e-08,
-        'weight_decay': 0,
-        'amsgrad': False       
+        "lr": 0.02,
+        "betas": (0.9, 0.999),
+        "eps": 1e-08,
+        "weight_decay": 0,
+        "amsgrad": False,
     },
     callbacks=[
-        dl.AccuracyCallback(input_key="logits", target_key="targets", topk_args=(1, 3, 5)),
+        dl.AccuracyCallback(
+            input_key="logits", target_key="targets", topk_args=(1, 3, 5)
+        ),
         dl.PrecisionRecallF1SupportCallback(
             input_key="logits", target_key="targets", num_classes=10
         ),
@@ -55,7 +63,5 @@
     minimize_valid_metric=True,
     verbose=True,
     load_best_on_end=True,
-    loggers={
-        "comet": logger
-    }
-)
+    loggers={"comet": logger},
+)

guides/tracking-ml-training/Comet_in_Notebooks.ipynb

@@ -27,7 +27,7 @@
     "id": "jS7jwZNSVH9_"
    },
    "source": [
-    "# Configuration through `comet.init()`"
+    "# Login to Comet"
    ]
   },
   {
@@ -40,7 +40,7 @@
    "source": [
     "import comet_ml\n",
     "\n",
-    "comet_ml.login(project_name=\"comet-in-notebooks\")"
+    "comet_ml.login()"
    ]
   },
   {
@@ -60,7 +60,7 @@
    },
    "outputs": [],
    "source": [
-    "experiment = comet_ml.Experiment()\n",
+    "experiment = comet_ml.Experiment(project_name=\"comet-in-notebooks\")\n",
     "\n",
     "for idx, value in enumerate(range(0, 100, 10)):\n",
     "    experiment.log_metric(\"accuracy\", value / 100, step=idx)"

integrations/model-deployment/seldon/notebooks/xgboost_seldon_aws.ipynb

@@ -45,7 +45,7 @@
    "outputs": [],
    "source": [
     "#### Import Comet ####\n",
-    "from comet_ml import Experiment, init\n",
+    "from comet_ml import Experiment, login\n",
     "\n",
     "#### Import Dependencies ####\n",
     "import xgboost as xgb\n",
@@ -68,7 +68,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "init()\n",
+    "login()\n",
     "\n",
     "experiment = Experiment(project_name=\"comet-example-xgboost-seldon\")"
    ]

integrations/model-evaluation/shap/shap-hello-world/shap-hello-world.py

@@ -1,5 +1,5 @@
 # -*- coding: utf-8 -*-
-from comet_ml import Experiment, init
+from comet_ml import Experiment, login
 
 import matplotlib
 import numpy as np
@@ -13,9 +13,9 @@
 matplotlib.use("agg")
 
 # Login to Comet if needed
-init(project_name="comet-example-shap-hello-world")
+login()
 
-experiment = Experiment()
+experiment = Experiment(project_name="comet-example-shap-hello-world")
 
 # Model / data parameters
 num_classes = 10

integrations/model-optimization/optuna/optuna-hello-world/optuna-hello-world.py

@@ -1,10 +1,10 @@
 # coding: utf-8
-from comet_ml import Experiment, init
+from comet_ml import Experiment, login
 
 import optuna
 
 # Login to Comet if needed
-init()
+login()
 
 
 def objective(trial):

integrations/model-training/pytorch/notebooks/Comet_Pytorch_TensorboardX.ipynb

@@ -170,7 +170,7 @@
    "source": [
     "Assuming you have already imported Comet at the beginning of your script, all you have to do now is set the `comet_config` argument when initializing TensorboardX's SummaryWriter. \n",
     "\n",
-    "`comet_config` is just a dictionary that allows you to set your workspace, project name and API key if you haven't already done so through `comet.init()`. \n",
+    "`comet_config` is just a dictionary that allows you to set your workspace, project name and API key if you haven't already done so through `comet.login()`. \n",
     "\n",
     "The dictionary has the following fields\n",
     "```\n",

integrations/model-training/pytorch/pytorch-mnist/pytorch-mnist-example.py

@@ -1,5 +1,5 @@
 # coding: utf-8
-from comet_ml import Experiment, init
+from comet_ml import Experiment, login
 from comet_ml.integration.pytorch import log_model, watch
 
 import torch
@@ -21,7 +21,7 @@
 
 
 # Login to Comet if needed
-init()
+login()
 
 experiment = Experiment(project_name="comet-example-pytorch-mnist")
 experiment.log_parameters(hyper_params)

integrations/model-training/pytorch/pytorch-rich-logging/pytorch-rich-logging-example.py

@@ -1,7 +1,7 @@
 # coding: utf-8
 import random
 
-from comet_ml import ConfusionMatrix, Experiment, init
+from comet_ml import ConfusionMatrix, Experiment, login
 from comet_ml.integration.pytorch import log_model
 
 import numpy as np
@@ -23,7 +23,7 @@
 }
 
 # Login to Comet if needed
-init()
+login()
 
 
 experiment = Experiment(project_name="comet-example-pytorch-rich-logging")

integrations/model-training/xgboost/xgboost-california/xgboost-california.py

@@ -2,7 +2,7 @@
 # coding: utf-8
 
 # Import Comet
-from comet_ml import Experiment, init
+from comet_ml import Experiment, login
 
 import pandas as pd
 from sklearn.datasets import fetch_california_housing
@@ -11,7 +11,7 @@
 import xgboost as xgb
 
 # Login to Comet if needed
-init()
+login()
 
 experiment = Experiment(project_name="comet-example-xgboost-california")
 

integrations/workflow-orchestration/kubeflow/kubeflow-hello-world/pipeline.py

@@ -2,14 +2,14 @@
 
 import os
 
-from comet_ml import init
+from comet_ml import login
 
 import kfp
 import kfp.dsl as dsl
 from kubernetes.client.models import V1EnvVar
 
 # Login to Comet if needed
-init()
+login()
 
 
 COMET_PROJECT_NAME = "comet-example-kubeflow-hello-world"

integrations/workflow-orchestration/metaflow/metaflow-hello-world/helloworld.py

@@ -1,6 +1,6 @@
 # coding: utf-8
 
-from comet_ml import init
+from comet_ml import login
 from comet_ml.integration.metaflow import comet_flow
 
 from metaflow import FlowSpec, step
@@ -46,6 +46,6 @@ def end(self):
 
 if __name__ == "__main__":
     # Login to Comet if needed
-    init()
+    login()
 
     HelloFlow()

integrations/workflow-orchestration/metaflow/metaflow-regression/metaflow-regression-example.py

@@ -1,6 +1,6 @@
 # coding: utf-8
 
-from comet_ml import init
+from comet_ml import login
 from comet_ml.integration.metaflow import comet_flow
 
 from metaflow import FlowSpec, JSONType, Parameter, card, step
@@ -122,6 +122,6 @@ def end(self):
 
 if __name__ == "__main__":
     # Login to Comet if needed
-    init()
+    login()
 
     RegressionFlow()

integrations/workflow-orchestration/vertex/vertex-hello-world/demo_pipeline.py

@@ -1,14 +1,14 @@
 # coding: utf-8
 import os
 
-from comet_ml import init
+from comet_ml import login
 
 import google.cloud.aiplatform as aip
 import kfp
 import kfp.v2.dsl as dsl
 
 # Login to Comet if needed
-init()
+login()
 
 
 COMET_PROJECT_NAME = "comet-example-vertex-hello-world"

integrations/workflow-orchestration/vertex/vertex-v2-hello-world/demo_pipeline.py

@@ -1,13 +1,13 @@
 # coding: utf-8
 import os
 
-from comet_ml import init
+from comet_ml import login
 
 import google.cloud.aiplatform as aip
 from kfp import compiler, dsl
 
 # Login to Comet if needed
-init()
+login()
 
 
 COMET_PROJECT_NAME = "comet-example-vertex-v2-hello-world"