tensorflow · bhuvanpkaruturi · Mar 3, 2026 · Mar 3, 2026 · Mar 3, 2026 · Mar 3, 2026
diff --git a/benchmarks/ResNet-50_v1.5_Performance_Comparison_TensorFlow_1.12_GCP.md b/benchmarks/ResNet-50_v1.5_Performance_Comparison_TensorFlow_1.12_GCP.md
@@ -156,7 +156,7 @@ sudo mkdir -p /data && sudo mount /dev/nvme0n1 /data
 ```
 ### Copies data from your GCS bucket created earlier to the local drive.
 sudo mkdir -p /data/imagenet && sudo chmod -R 777 /data
-gsutil -m cp -r gs://<your bucket with imagenet>/imagenet/* /data/imagenet/
+gcloud storage cp --recursive gs://<your bucket with imagenet>/imagenet/* /data/imagenet/
 ```
 
 4. Install TensorFlow 1.12 compiled with CUDA 10.0, cuDNN 7.3, and AVX2.

diff --git a/benchmarks/ShapeMask_Performance_Comparison_TensorFlow_1.14_GCP.md b/benchmarks/ShapeMask_Performance_Comparison_TensorFlow_1.14_GCP.md
@@ -54,7 +54,7 @@ export USER=weicheng  # Your user name.
 export STORAGE_BUCKET=gs://${USER}-data
 
 # Create storage bucket.
-gsutil mb $STORAGE_BUCKET
+gcloud storage buckets create $STORAGE_BUCKET
 
 # Download COCO data.
 mkdir ~/data
@@ -66,16 +66,16 @@ bash download_and_preprocess_coco.sh ~/data/coco
 # Create coco directory under the bucket.
 mkdir coco
 touch coco/empty.txt
-gsutil cp -r coco $STORAGE_BUCKET
+gcloud storage cp --recursive coco $STORAGE_BUCKET
 
 # Move data over to bucket.
-gsutil -m cp data/coco/*.tfrecord gs://${USER}-data/coco
-gsutil -m cp data/coco/raw-data/annotations/*.json gs://${USER}-data/coco
+gcloud storage cp data/coco/*.tfrecord gs://${USER}-data/coco
+gcloud storage cp data/coco/raw-data/annotations/*.json gs://${USER}-data/coco
 
 # Create shapemask directory under the bucket.
 mkdir shapemask_exp
 touch shapemask_exp/empty.txt
-gsutil cp -r shapemask_exp gs://${USER}-data/
+gcloud storage cp --recursive shapemask_exp gs://${USER}-data/
 
 # Back to home directory.
 cd ~

diff --git a/models/experimental/inference/setup-pool.sh b/models/experimental/inference/setup-pool.sh
@@ -66,7 +66,7 @@ function check_tpu_tf_versions() {
 }
 
 function check_model_exists() {
-  num_versions=$(expr $(gsutil ls ${MODEL_BASE_PATH?} | wc | awk '{print $1}')-1)
+  num_versions=$(expr $(gcloud storage ls ${MODEL_BASE_PATH?} | wc | awk '{print $1}')-1)
   if [[ $num_versions < 1 ]]; then
     err "The MODEL_BASE_PATH provided is not valid."
   fi

diff --git a/models/experimental/mnist_jupyter/Cloud-TPU-Demo.ipynb b/models/experimental/mnist_jupyter/Cloud-TPU-Demo.ipynb
@@ -108,10 +108,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!gsutil mb -c regional -l us-central1 gs://$GCS_DATA_BUCKET\n",
-    "!gsutil mb -c regional -l us-central1 gs://$GCS_CKPT_BUCKET\n",
+    "!gcloud storage buckets create --default-storage-class=regional --location=us-central1 gs://$GCS_DATA_BUCKET\n",
+    "!gcloud storage buckets create --default-storage-class=regional --location=us-central1 gs://$GCS_CKPT_BUCKET\n",
     "\n",
-    "!gsutil iam ch serviceAccount:`gcloud alpha compute tpus describe $TPU_NAME | grep serviceAccount | cut -d' ' -f2`:admin gs://$GCS_DATA_BUCKET gs://$GCS_CKPT_BUCKET && echo 'Successfully set permissions!'"
+    "!gcloud storage buckets add-iam-policy-binding gs://$GCS_DATA_BUCKET --member=serviceAccount:`gcloud alpha compute tpus describe $TPU_NAME | grep serviceAccount | cut -d' ' -f2` --role=admin && gcloud storage buckets add-iam-policy-binding gs://$GCS_CKPT_BUCKET --member=serviceAccount:`gcloud alpha compute tpus describe $TPU_NAME | grep serviceAccount | cut -d' ' -f2` --role=admin && echo 'Successfully set permissions!'"
    ]
   },
   {

diff --git a/models/official/detection/projects/openseg/OpenSeg_demo.ipynb b/models/official/detection/projects/openseg/OpenSeg_demo.ipynb
@@ -204,10 +204,8 @@
             "Copying gs://cloud-tpu-checkpoints/detection/projects/openseg/colab/exported_model/graph_def.txt...\n",
             "Copying gs://cloud-tpu-checkpoints/detection/projects/openseg/colab/exported_model/saved_model.pb...\n",
             "-\n",
-            "==\u003e NOTE: You are performing a sequence of gsutil operations that may\n",
-            "run significantly faster if you instead use gsutil -m cp ... Please\n",
-            "see the -m section under \"gsutil help options\" for further information\n",
-            "about when gsutil -m can be advantageous.\n",
+            "==\u003e NOTE: You are performing a sequence of gcloud storage operations that may\n",
+            "run significantly faster if you instead use gcloud storage cp ... Please\n",            "see the -m section under \"gcloud storage --help\" for further information\n",            "about when gsutil -m can be advantageous.\n",
             "\n",
             "Copying gs://cloud-tpu-checkpoints/detection/projects/openseg/colab/exported_model/variables/variables.data-00000-of-00001...\n",
             "Copying gs://cloud-tpu-checkpoints/detection/projects/openseg/colab/exported_model/variables/variables.index...\n",
@@ -217,10 +215,7 @@
             "Copying gs://cloud-tpu-checkpoints/detection/projects/openseg/colab/examples/camera.jpg...\n",
             "Copying gs://cloud-tpu-checkpoints/detection/projects/openseg/colab/examples/police_car.jpg...\n",
             "/ [3 files][465.1 KiB/465.1 KiB]                                                \n",
-            "==\u003e NOTE: You are performing a sequence of gsutil operations that may\n",
-            "run significantly faster if you instead use gsutil -m cp ... Please\n",
-            "see the -m section under \"gsutil help options\" for further information\n",
-            "about when gsutil -m can be advantageous.\n",
+            "==\u003e NOTE: You are performing a sequence of gcloud storage operations that may\n",            "run significantly faster if you instead use gcloud storage cp ... Please\n",            "gcloud storage commands are parallel by default; a flag like -m is not needed.\n",            "about when gsutil -m can be advantageous.\n",
             "\n",
             "Copying gs://cloud-tpu-checkpoints/detection/projects/openseg/colab/examples/telephone_kiosk.jpg...\n",
             "/ [4 files][665.2 KiB/665.2 KiB]                                                \n",
@@ -230,9 +225,8 @@
       ],
       "source": [
         "#@title Download files \n",
-        "!gsutil cp -r gs://cloud-tpu-checkpoints/detection/projects/openseg/colab/exported_model ./\n",
-        "!gsutil cp -r gs://cloud-tpu-checkpoints/detection/projects/openseg/colab/examples ./"
-      ]
+        "!gcloud storage cp --recursive gs://cloud-tpu-checkpoints/detection/projects/openseg/colab/exported_model .\n",
+        "!gcloud storage cp --recursive gs://cloud-tpu-checkpoints/detection/projects/openseg/colab/examples ./"      ]
     },
     {
       "cell_type": "code",

diff --git a/models/official/detection/projects/vild/ViLD_demo.ipynb b/models/official/detection/projects/vild/ViLD_demo.ipynb
@@ -132,9 +132,7 @@
    },
    "source": [
     "#@title Download files\n",
-    "!gsutil cp -r gs://cloud-tpu-checkpoints/detection/projects/vild/colab/image_path_v2 ./\n",
-    "!gsutil cp -r gs://cloud-tpu-checkpoints/detection/projects/vild/colab/examples ./"
-   ],
+"!gcloud storage cp --recursive gs://cloud-tpu-checkpoints/detection/projects/vild/colab/image_path_v2 ./\n",    "!gcloud storage cp --recursive gs://cloud-tpu-checkpoints/detection/projects/vild/colab/examples ./"   ],
    "execution_count": null,
    "outputs": [
     {

diff --git a/models/official/resnet/README.md b/models/official/resnet/README.md
@@ -60,7 +60,7 @@ created by `ctpu up`, this argument may not be necessary.)
 `$MODEL_DIR` is a GCS location (a URL starting with `gs://` where both the GCE
 VM and the associated Cloud TPU have write access, something like `gs://userid-
 dev-imagenet-output/model`.  (TensorFlow can't create the bucket; you have to
-create it with `gsutil mb <bucket>`.)  This bucket is used to save checkpoints
+create it with `gcloud storage buckets create <bucket>`.)  This bucket is used to save checkpoints
 and the training result, so that the training steps are cumulative when you
 reuse the model directory.  If you do 1000 steps, for example, and you reuse the
 model directory, on a subsequent run, it will skip the first 1000 steps, because

diff --git a/models/official/retinanet/README.md b/models/official/retinanet/README.md
@@ -52,7 +52,7 @@ You can create a bucket using the
 the command line with gsutil:
 
 ```
-gsutil mb ${GCS_BUCKET}
+gcloud storage buckets create ${GCS_BUCKET}
 ```
 
 ## Preparing the COCO dataset
@@ -86,8 +86,8 @@ training.  We can use `gsutil` to copy the files over.  We also want to save the
 annotation files: we use these to validate our model performance:
 
 ```
-gsutil -m cp ./data/dir/coco/*.tfrecord ${GCS_BUCKET}/coco
-gsutil cp ./data/dir/coco/raw-data/annotations/*.json ${GCS_BUCKET}/coco
+gcloud storage cp ./data/dir/coco/*.tfrecord ${GCS_BUCKET}/coco
+gcloud storage cp ./data/dir/coco/raw-data/annotations/*.json ${GCS_BUCKET}/coco
 ```
 
 ## Installing extra packages
@@ -221,7 +221,7 @@ test that we can read our model directory and validation files.
 # export GCS_BUCKET as above
 
 # Copy over the annotation file we created during preprocessing
-gsutil cp ${GCS_BUCKET}/coco/instances_val2017.json .
+gcloud storage cp ${GCS_BUCKET}/coco/instances_val2017.json .
 
 python tpu/models/official/retinanet/retinanet_main.py  \
  --use_tpu=False \

diff --git a/tools/colab/bert_finetuning_with_cloud_tpus.ipynb b/tools/colab/bert_finetuning_with_cloud_tpus.ipynb
@@ -4236,8 +4236,7 @@
         "# Setup task specific model and TPU running config.\n",
         "BERT_PRETRAINED_DIR = 'gs://cloud-tpu-checkpoints/bert/' + BERT_MODEL \n",
         "print('***** BERT pretrained directory: {} *****'.format(BERT_PRETRAINED_DIR))\n",
-        "!gsutil ls $BERT_PRETRAINED_DIR\n",
-        "\n",
+        "!gcloud storage ls $BERT_PRETRAINED_DIR\n",        "\n",
         "CONFIG_FILE = os.path.join(BERT_PRETRAINED_DIR, 'bert_config.json')\n",
         "INIT_CHECKPOINT = os.path.join(BERT_PRETRAINED_DIR, 'bert_model.ckpt')\n",
         "\n",

diff --git a/tools/ctpu/tutorial.md b/tools/ctpu/tutorial.md
@@ -148,7 +148,7 @@ variable you set in the last step will be automatically substituted so you can
 copy-paste the following commands unmodified):
 
 ```bash
-gsutil cp -r ./data gs://$GCS_BUCKET_NAME/mnist/data
+gcloud storage cp --recursive ./data gs://$GCS_BUCKET_NAME/mnist/data
 ```
 
 ### Train your model ###

diff --git a/tools/datasets/download_and_preprocess_coco_k8s.yaml b/tools/datasets/download_and_preprocess_coco_k8s.yaml
@@ -27,8 +27,8 @@ spec:
             DEBIAN_FRONTEND=noninteractive apt-get update &&
             cd /tensorflow_tpu_models/tools/datasets &&
             bash download_and_preprocess_coco.sh /scratch-dir &&
-            gsutil -m cp /scratch-dir/*.tfrecord ${DATA_BUCKET}/coco &&
-            gsutil cp /scratch-dir/raw-data/annotations/*.json ${DATA_BUCKET}/coco
+            gcloud storage cp /scratch-dir/*.tfrecord ${DATA_BUCKET}/coco &&
+            gcloud storage cp /scratch-dir/raw-data/annotations/*.json ${DATA_BUCKET}/coco
         env:
           # [REQUIRED] Must specify the Google Cloud Storage location where the
           # COCO dataset will be stored.

diff --git a/tools/datasets/jpeg_to_tf_record.py b/tools/datasets/jpeg_to_tf_record.py
@@ -204,7 +204,7 @@ def convert_to_example(csvline, categories):
   # and this could cause confusion if earlier run has 0000-of-0005, for eg
   if on_cloud:
     try:
-      subprocess.check_call('gsutil -m rm -r {}'.format(OUTPUT_DIR).split())
+      subprocess.check_call('gcloud storage rm --recursive {}'.format(OUTPUT_DIR).split())
     except subprocess.CalledProcessError:
       pass
   else: