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DENG-6965 Track the trained model as W&B Artifact #41

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DENG-6965 Track the trained model as W&B Artifact #41

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DENG-6965 Track the trained model as W&B Artifact
abhi-agg Dec 10, 2024
30e8a35
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abhi-agg Dec 13, 2024
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11 changes: 11 additions & 0 deletions examples/image_classifier/image_classifier_flow.py
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Original file line number Diff line number Diff line change
Expand Up @@ -83,6 +83,7 @@ def train(self):
import wandb
import os

tracking_run = {}
if not self.offline_wandb:
tracking_run = wandb.init(project=os.getenv("WANDB_PROJECT"))
wandb_url = tracking_run.get_url()
Expand Down Expand Up @@ -144,6 +145,16 @@ def train(self):
buffer = BytesIO()
torch.save(image_classifier_model.state_dict(), buffer)
self.model_state_dict_bytes = buffer.getvalue()

if not self.offline_wandb:
# Save trained model locally and then track it in W&B
torch.save(image_classifier_model.state_dict(), "./trained_model.pt")
model_artifact = wandb.Artifact(
name="trained_image_classifier", type="model"
)
model_artifact.add_file(local_path="./trained_model.pt")
tracking_run.log_artifact(model_artifact)

self.next(self.evaluate)

# Test the model on the test data
Expand Down