Add sparse and ragged options to TextVectorization output
Add sparse and ragged options to TextVectorization output

Sparse will only apply when output_mode is "one_hot", "multi_hot",
"count", or "tf_idf" and the last dimension of the output contains
bins for every element in the vocab. Sparse will be a more efficient
output option when vocab size is large.

Ragged will only apply when output_mode is "int", and will output
a ragged tensor after string splitting where the final dimension
contains ragged vocab indices of variable length.

PiperOrigin-RevId: 391415472
Change-Id: I6f600fb476667b8af8328b051392bdcf9f9b3266

Intel-Corporation/tensorflow,tensorflow/tensorflow-pywrap_tf_optimizer,Intel-tensorflow/tensorflow,gautam1858/tensorflow,gautam1858/tensorflow,tensorflow/tensorflow-pywrap_saved_model,Intel-Corporation/tensorflow,yongtang/tensorflow,tensorflow/tensorflow-pywrap_tf_optimizer,paolodedios/tensorflow,tensorflow/tensorflow-pywrap_tf_optimizer,tensorflow/tensorflow,tensorflow/tensorflow-pywrap_saved_model,yongtang/tensorflow,paolodedios/tensorflow,tensorflow/tensorflow-pywrap_tf_optimizer,tensorflow/tensorflow-experimental_link_static_libraries_once,paolodedios/tensorflow,tensorflow/tensorflow-pywrap_saved_model,paolodedios/tensorflow,tensorflow/tensorflow-pywrap_saved_model,paolodedios/tensorflow,tensorflow/tensorflow-experimental_link_static_libraries_once,paolodedios/tensorflow,tensorflow/tensorflow,karllessard/tensorflow,gautam1858/tensorflow,karllessard/tensorflow,Intel-tensorflow/tensorflow,karllessard/tensorflow,karllessard/tensorflow,tensorflow/tensorflow,tensorflow/tensorflow-pywrap_saved_model,tensorflow/tensorflow-pywrap_tf_optimizer,tensorflow/tensorflow-pywrap_saved_model,gautam1858/tensorflow,Intel-tensorflow/tensorflow,tensorflow/tensorflow-pywrap_saved_model,paolodedios/tensorflow,Intel-Corporation/tensorflow,yongtang/tensorflow,tensorflow/tensorflow,gautam1858/tensorflow,Intel-Corporation/tensorflow,tensorflow/tensorflow-pywrap_tf_optimizer,yongtang/tensorflow,Intel-Corporation/tensorflow,karllessard/tensorflow,paolodedios/tensorflow,Intel-Corporation/tensorflow,karllessard/tensorflow,tensorflow/tensorflow,tensorflow/tensorflow-experimental_link_static_libraries_once,gautam1858/tensorflow,Intel-tensorflow/tensorflow,tensorflow/tensorflow-pywrap_tf_optimizer,yongtang/tensorflow,gautam1858/tensorflow,tensorflow/tensorflow,tensorflow/tensorflow,Intel-tensorflow/tensorflow,Intel-tensorflow/tensorflow,karllessard/tensorflow,tensorflow/tensorflow-pywrap_saved_model,tensorflow/tensorflow-pywrap_saved_model,yongtang/tensorflow,tensorflow/tensorflow-experimental_link_static_libraries_once,tensorflow/tensorflow-experimental_link_static_libraries_once,tensorflow/tensorflow-pywrap_saved_model,paolodedios/tensorflow,tensorflow/tensorflow-experimental_link_static_libraries_once,karllessard/tensorflow,yongtang/tensorflow,Intel-tensorflow/tensorflow,tensorflow/tensorflow,Intel-tensorflow/tensorflow,tensorflow/tensorflow,Intel-tensorflow/tensorflow,Intel-Corporation/tensorflow,yongtang/tensorflow,yongtang/tensorflow,tensorflow/tensorflow-pywrap_tf_optimizer,Intel-Corporation/tensorflow,tensorflow/tensorflow-experimental_link_static_libraries_once,paolodedios/tensorflow,tensorflow/tensorflow-pywrap_tf_optimizer,gautam1858/tensorflow,tensorflow/tensorflow-experimental_link_static_libraries_once,gautam1858/tensorflow,yongtang/tensorflow,tensorflow/tensorflow-experimental_link_static_libraries_once,gautam1858/tensorflow,Intel-tensorflow/tensorflow,yongtang/tensorflow,Intel-tensorflow/tensorflow,tensorflow/tensorflow,gautam1858/tensorflow,tensorflow/tensorflow,tensorflow/tensorflow-pywrap_saved_model,karllessard/tensorflow,gautam1858/tensorflow,tensorflow/tensorflow-experimental_link_static_libraries_once,karllessard/tensorflow,tensorflow/tensorflow-experimental_link_static_libraries_once,tensorflow/tensorflow-pywrap_tf_optimizer,karllessard/tensorflow,paolodedios/tensorflow,tensorflow/tensorflow-pywrap_tf_optimizer