Whisper large in SparkNlp (Message tensorflow.GraphDef exceeds maximum protobuf size of 2GB)
my code in 
https://colab.research.google.com/drive/1dkIfVZf8WtQAVLKaSt8s95_29BHcLOlw#scrollTo=8xN4MqZagxCQ All PyTorch model weights were used when initializing WhisperExport.

All the weights of WhisperExport were initialized from the PyTorch model.
If your task is similar to the task the model of the checkpoint was trained on, you can already use WhisperExport for predictions without further training.
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-4-3156f99a4cea> in <cell line: 207>()
    206 
    207 model_wrapping = ModelWrapping(
--> 208     whisper_model.make_encoder_serving(),
    209     whisper_model.make_decoder_init_serving(),
    210     whisper_model.make_decoder_serving(),

11 frames
/usr/local/lib/python3.10/dist-packages/tensorflow/python/framework/importer.py in _import_graph_def_internal(graph_def, input_map, return_elements, validate_colocation_constraints, name, producer_op_list)
    495   # _ProcessNewOps.
    496   with graph._mutation_lock():  # pylint: disable=protected-access
--> 497     with c_api_util.tf_buffer(graph_def.SerializeToString()) as serialized:
    498       try:
    499         with graph._c_graph.get() as c_graph:  # pylint: disable=protected-access

ValueError: Message tensorflow.GraphDef exceeds maximum protobuf size of 2GB: 2549145890 Please help me. Thank u very much @minhduc210196,
I do not have access to the link you have provided. Could you please provide the required permissions to view the files.

Also the error message **ValueError: Message tensorflow.GraphDef exceeds maximum protobuf size of 2GB** indicates that the TensorFlow GraphDef object, which is a protocol buffer exceeds the maximum allowed size of 2GB. 

This can happen when the graph is too large or has too many nodes. Could you please try reducing the size of the graph by removing unnecessary nodes or operations. Additionally, you can split the graph into smaller sub-graphs and run them separately.
https://github.com/tensorflow/tensorflow/issues/47326
https://github.com/tensorflow/tensorflow/issues/55692


Thank you! This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activity occurs. Thank you. This issue was closed because it has been inactive for 7 days since being marked as stale. Please reopen if you'd like to work on this further. Are you satisfied with the resolution of your issue?
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Issue Type
Bug

Source
source

Tensorflow Version
2.10

Custom Code
No

Google colab

Mobile device
No response

Python version
3.9

Bazel version
No response

GCC/Compiler version
No response

CUDA/cuDNN version
11.4/8.1.0

GPU model and memory
A100 40GB