tensorflow · gurusai-voleti · Sep 8, 2026 · Sep 8, 2026
@@ -14,7 +14,7 @@ gcloud config set project ${PROJECT_ID}
 ```
 4. Create a Cloud Storage bucket using the following command:
 ```
-gsutil mb -p ${PROJECT_ID} -c standard -l europe-west4 -b on gs://your-bucket-name
+gcloud storage buckets create --project=${PROJECT_ID} --default-storage-class=standard --location=europe-west4 --uniform-bucket-level-access gs://your-bucket-name
 ```
 This Cloud Storage bucket stores the data you use to train your model and the training results.
 5. Launch a Compute Engine VM and Cloud TPU using the ctpu up command.
@@ -100,7 +100,7 @@ $ ctpu status --zone=your-zone
 ```
 4. Run gsutil as shown, replacing your-bucket with the name of the Cloud Storage bucket you created for this tutorial:
 ```
-$ gsutil rm -r gs://your-bucket
+$ gcloud storage rm --recursive gs://your-bucket
 ```
 
 

@@ -59,7 +59,7 @@ export SPIECE_DIR=~/cased_spiece/
 export SPIECE_MODEL=${SPIECE_DIR}/cased_spiece.model
 export DATASETS_DIR=gs://some_bucket/datasets
 mkdir -p ${SPIECE_DIR}
-gsutil cp gs://cloud-tpu-checkpoints/xlnet/cased_spiece.model ${SPIECE_DIR}
+gcloud storage cp gs://cloud-tpu-checkpoints/xlnet/cased_spiece.model ${SPIECE_DIR}
 ```
 
 
@@ -134,7 +134,7 @@ Then to process the dataset into TFRecords, run the following commands:
 ```shell
 python3 preprocess_squad_data.py --spiece_model_file=${SPIECE_MODEL} --train_file=${SQUAD_DIR}/train-v2.0.json --predict_file=${SQUAD_DIR}/dev-v2.0.json --output_dir=${DATASETS_DIR}/squad --uncased=False --max_seq_length=512 --num_proc=1 --proc_id=0
 
-gsutil cp ${SQUAD_DIR}/dev-v2.0.json ${DATASETS_DIR}/squad
+gcloud storage cp ${SQUAD_DIR}/dev-v2.0.json ${DATASETS_DIR}/squad
 ```
 
 ## Fine-tuning with XLNet

@@ -21,7 +21,7 @@ pytorch longformer tokenized data to tf_records.
 Option 1. Use our saved checkpoint of `allenai/longformer-base-4096` stored in cloud storage
 
 ```bash
-gsutil cp -r gs://model-garden-ucsd-zihan/longformer-4096 .
+gcloud storage cp --recursive gs://model-garden-ucsd-zihan/longformer-4096 .
 ```
 Option 2. Create it directly
 

@@ -42,7 +42,7 @@ training, using mobilebert as an exmaple:
 ```shell
 
 # First, Download the pre-trained floating point model as QAT needs to finetune it.
-gsutil cp gs://tf_model_garden/nlp/qat/mobilebert/mobilebert_fp32_ckpt.tar.gz /tmp/qat/
+gcloud storage cp gs://tf_model_garden/nlp/qat/mobilebert/mobilebert_fp32_ckpt.tar.gz /tmp/qat/
 
 # Extract the checkpoint.
 tar -xvzf /tmp/qat/mobilebert_fp32_ckpt.tar.gz

@@ -98,7 +98,7 @@ using object detection as an example:
 ```shell
 
 # First download the pre-trained floating point model as QAT needs to finetune it.
-gsutil cp gs://tf_model_garden/vision/qat/mobilenetv2_ssd_coco/mobilenetv2_ssd_i256_ckpt.tar.gz /tmp/qat/
+gcloud storage cp gs://tf_model_garden/vision/qat/mobilenetv2_ssd_coco/mobilenetv2_ssd_i256_ckpt.tar.gz /tmp/qat/
 
 # Extract the checkpoint.
 tar -xvzf /tmp/qat/mobilenetv2_ssd_i256_ckpt.tar.gz

@@ -131,7 +131,7 @@ def upload_image_results_to_storage_bucket(
     try:
       commands = [
           f"rm -r {os.path.basename(input_directory)}",
-          f"gsutil -m cp -r {prediction_folder} {output_directory}",
+          f"gcloud storage cp --recursive {prediction_folder} {output_directory}",
           f"rm -r {prediction_folder}",
       ]
       subprocess.run(" && ".join(commands), shell=True, check=True)

@@ -198,7 +198,7 @@ def test_upload_image_results_to_storage_bucket_success(self):
 
     self.mock_subprocess_run.assert_called_once()
     args, _ = self.mock_subprocess_run.call_args
-    self.assertIn(f"gsutil -m cp -r {pred_dir} {output_dir}", args[0])
+    self.assertIn(f"gcloud storage cp --recursive {pred_dir} {output_dir}", args[0])
 
   def test_upload_image_results_to_storage_bucket_failure(self):
     input_dir = "/tmp/input"

@@ -29,14 +29,14 @@ def copy(path: str) -> None:
   Args:
     path: path of the video in GCS bucket.
   """
-  gsutil_command = f"gsutil cp -r {path} ."
+  gsutil_command = f"gcloud storage cp --recursive {path} ."
   subprocess.run(gsutil_command, shell=True, check=True)
 
 
 def move(file_path: str, destination_bucket_path: str) -> None:
   """Moves a video file or directory of image files.
 
-  This function uses the 'gsutil' command-line utility to move a file or
+  This function uses the 'gcloud' command-line utility to move a file or
   directory to a GCS bucket. If the given file path is a directory, it moves
   all contents recursively. The function executes the appropriate 'gsutil'
   command based on whether the provided file path is a file or a directory.
@@ -48,9 +48,10 @@ def move(file_path: str, destination_bucket_path: str) -> None:
       will be moved to. This path should be in the format
       'gs://bucket-name/path/to/destination'.
   """
+  destination_bucket_path = destination_bucket_path.rstrip('/') + '/'
   if os.path.isdir(file_path):
-    gsutil_command = f"gsutil -m mv -r {file_path} {destination_bucket_path}"
+    gsutil_command = f"gcloud storage mv {file_path} {destination_bucket_path}"
   else:
-    gsutil_command = f"gsutil mv {file_path} {destination_bucket_path}"
+    gsutil_command = f"gcloud storage mv {file_path} {destination_bucket_path}"
 
   subprocess.run(gsutil_command, shell=True, check=True)
@@ -100,7 +100,7 @@ images to the source GCS bucket created by the script. The script output will
 provide the name of the bucket.
 
 ```bash
-gsutil cp your-local-image.jpg gs://<source-bucket-name>/
+gcloud storage cp your-local-image.jpg gs://<source-bucket-name>/
 ```
 ---
 

@@ -29,14 +29,14 @@ cd milk_pouch_project
 # NOTE: Adjust the grep pattern if other image types are expected.
 echo "=== DEBUGGING START ==="
 echo "DEBUG: gcs_path variable is: '${gcs_path}'"
-echo "DEBUG: Running 'gsutil ls \"${gcs_path}\"' to check accessibility:"
-gsutil ls "${gcs_path}" || echo "❌ gsutil ls failed"
-echo "DEBUG: Running 'gsutil ls -r \"${gcs_path}\" | head -n 10' to check content:"
-gsutil ls -r "${gcs_path}" | head -n 10 || echo "❌ gsutil recursive ls failed"
+echo "DEBUG: Running 'gcloud storage ls \"${gcs_path}\"' to check accessibility:"
+gcloud storage ls "${gcs_path}" || echo "❌ gcloud storage ls failed"
+echo "DEBUG: Running 'gcloud storage ls --recursive \"${gcs_path}\" | head -n 10' to check content:"
+gcloud storage ls --recursive "${gcs_path}" | head -n 10 || echo "❌ gsutil recursive ls failed"
 echo "=== DEBUGGING END ==="
 
 echo "🖨️ Listing image files from GCS bucket: $gcs_path"
-mapfile -t all_gcs_files < <(gsutil ls -r "${gcs_path}" | grep -iE '\.(png|jpg|jpeg)$' | grep -v "/predictions/" | grep -v "/processed/")
+mapfile -t all_gcs_files < <(gcloud storage ls --recursive "${gcs_path}" | grep -iE '\.(png|jpg|jpeg)$' | grep -v "/predictions/" | grep -v "/processed/")
 num_files=${#all_gcs_files[@]}
 
 if (( num_files == 0 )); then
@@ -77,7 +77,7 @@ for (( i=0; i<num_files; i+=batch_size )); do
 
   # Copy current batch files from GCS
   echo "🖨️ Copying $num_in_batch files from GCS to input_images/..."
-  gsutil -m cp "${current_batch[@]}" input_images/
+  gcloud storage cp "${current_batch[@]}" input_images/
 
   # Extract objects
   echo "🔎 Extracting objects from images..."
@@ -96,7 +96,7 @@ for (( i=0; i<num_files; i+=batch_size )); do
   # Move predictions back to GCS
   if [ -d "predictions" ] && [ -n "$(find predictions -type f -print -quit)" ]; then
     echo "🖨️ Moving predictions for this batch back to GCS bucket: $gcs_path"
-    gsutil -m cp -r predictions/ "$gcs_path"
+    gcloud storage cp --recursive predictions/ "$gcs_path"
   else
     echo "⚠️ No predictions generated for this batch."
   fi
@@ -128,7 +128,7 @@ for (( i=0; i<num_files; i+=batch_size )); do
     # If the destination directory changes, flush the current batch
     if [[ "$dest_dir" != "$current_move_dir" ]]; then
       if (( ${#current_move_batch[@]} > 0 )); then
-        gsutil -m mv "${current_move_batch[@]}" "$current_move_dir"
+        gcloud storage mv "${current_move_batch[@]}" "$current_move_dir"
         current_move_batch=()
       fi
       current_move_dir="$dest_dir"
@@ -138,7 +138,7 @@ for (( i=0; i<num_files; i+=batch_size )); do
 
   # Flush any remaining files
   if (( ${#current_move_batch[@]} > 0 )); then
-    gsutil -m mv "${current_move_batch[@]}" "$current_move_dir"
+    gcloud storage mv "${current_move_batch[@]}" "$current_move_dir"
   fi
 
   unset current_move_batch
-Original file line number
+Diff line change
@@ Expand Up @@
     provide the name of the bucket.
     ```bash
-    gsutil cp your-local-image.jpg gs://<source-bucket-name>/
+    gcloud storage cp your-local-image.jpg gs://<source-bucket-name>/
     ```
     ---
@@ Expand Down @@