parameters: (self, table)
docstring: Initialize the resource op with a pyarrow.Table
docstring_summary: Initialize the resource op with a pyarrow.Table
docstring_tokens: Initialize the resource op with a pyarrow . Table
function: def init_resource_op(self, table):
          """Initialize the resource op with a pyarrow.Table"""
          with tf.name_scope("ArrowIOTensor") as scope:
  
              # Serialize the schema to send to the kernel
              schema_buffer = table.schema.serialize()
  
              # References to prevent data from being freed until op is evaluated
              self.arrow_data_refs = [table, schema_buffer]
  
              # Get buffer addresses as long ints
              schema_buffer_addr = schema_buffer.address
              schema_buffer_size = schema_buffer.size
              array_tuple = _extract_table_arrays(table)
              array_buffer_addrs, array_buffer_sizes, array_lengths = array_tuple
  
              # Create the Arrow readable resource op
              resource_op = core_ops.io_arrow_readable_from_memory_init(
                  schema_buffer_addr,
                  schema_buffer_size,
                  array_buffer_addrs,
                  array_buffer_sizes,
                  array_lengths,
                  container=scope,
                  shared_name="pyarrow.Table{}/{}".format(
                      table.schema.names, uuid.uuid4().hex
                  ),
              )
  
              return resource_op
function_tokens: def init_resource_op ( self , table ) : with tf . name_scope ( "ArrowIOTensor" ) as scope : # Serialize the schema to send to the kernel schema_buffer = table . schema . serialize ( ) # References to prevent data from being freed until op is evaluated self . arrow_data_refs = [ table , schema_buffer ] # Get buffer addresses as long ints schema_buffer_addr = schema_buffer . address schema_buffer_size = schema_buffer . size array_tuple = _extract_table_arrays ( table ) array_buffer_addrs , array_buffer_sizes , array_lengths = array_tuple # Create the Arrow readable resource op resource_op = core_ops . io_arrow_readable_from_memory_init ( schema_buffer_addr , schema_buffer_size , array_buffer_addrs , array_buffer_sizes , array_lengths , container = scope , shared_name = "pyarrow.Table{}/{}" . format ( table . schema . names , uuid . uuid4 ( ) . hex ) , ) return resource_op