Merge pull request #333 from gurusai-voleti:ai-gsutil-migration-0db8d603601c4a51af0e15c59165731c

PiperOrigin-RevId: 875764071

Author: Google-ML-Automation

README.md

@@ -178,7 +178,7 @@ After installation completes, run the training script.
 
   ```bash
   BUCKET_NAME=my-bucket
-  gsutil -m cp -r $TFRECORDS_DATASET_DIR gs://$BUCKET_NAME/${TFRECORDS_DATASET_DIR##*/}
+  gcloud storage cp --recursive $TFRECORDS_DATASET_DIR gs://$BUCKET_NAME/${TFRECORDS_DATASET_DIR##*/}
   ```
 
   Now run the training command:
@@ -705,4 +705,3 @@ This script will automatically format your code with `pyink` and help you identi
 
 The full suite of -end-to end tests is in `tests` and `src/maxdiffusion/tests`. We run them with a nightly cadance.
 
-

src/maxdiffusion/pedagogical_examples/save_sd_checkpoint.py

@@ -17,7 +17,7 @@
 """Load and save a checkpoint. This is useful for uploading checkpoints to gcs
 and later loading them from gcs directly.
 After calling this script, use gsutil to upload the weights to a bucket:
-gsutil -m cp -r sd-model-finetuned gs://<your-bucket>/sd_checkpoint/
+gcloud storage cp --recursive sd-model-finetuned gs://<your-bucket>/sd_checkpoint/
 """
 
 from typing import Sequence

src/maxdiffusion/pedagogical_examples/save_sdxl_checkpoint.py

@@ -17,7 +17,7 @@
 """Load and save a checkpoint. This is useful for uploading checkpoints to gcs
 and later loading them from gcs directly.
 After calling this script, use gsutil to upload the weights to a bucket:
-gsutil -m cp -r sdxl-model-finetuned gs://<your-bucket>/sdxl_1.0_base/
+gcloud storage cp --recursive sdxl-model-finetuned gs://<your-bucket>/sdxl_1.0_base/
 """
 
 from typing import Sequence