How to load a dataset from google cloud storage with tensorflow cloud?

[Prikshet Sharma]

Tensorflow cloud configuration:

  GCP_BUCKET = "stereo-train"

  tfc.run(
    requirements_txt="requirements.txt",
    chief_config=tfc.MachineConfig(
      cpu_cores=8,
      memory=30,
      accelerator_type=tfc.AcceleratorType.NVIDIA_TESLA_T4,
      accelerator_count=1,
    ),
    docker_image_bucket_name=GCP_BUCKET,
  )

And I have a bucket called gs://stereo-train that contains the dataset. The exact location of the dataset is:

gs://stereo-train/data_scene_flow/training/dat

However, when using this location like so:

tf.keras.preprocessing.image_dataset_from_directory("gs://stereo-train/data_scene_flow/training/dat", image_size=(375,1242),\
                                                         batch_size=6, shuffle=False, label_mode=None)

Behavior:

getting the error that "gs://stereo-train/data_scene_flow/training/dat" doesn't exist

Expected behavior:
tf.keras.preprocessing.image_dataset_from_directory should know that there's a gs bucket associated with the account and the dataset should be loaded.

[Eddy Decena]

I tried to do the same locally and it gave me the same error. I think that is a tf.keras/keras error you can open an issue in the official TensorFlow repository