class_docstr: Symbolic data buffer in TVM.
  
  Buffer provide a way to represent data layout
  specialization of data structure in TVM.
  
  Do not construct directly, use :py:func:`~decl_buffer` instead.
  See the documentation of :py:func:`decl_buffer` for more details.
  
  See Also
  --------
  decl_buffer : Declare a buffer
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docstr: Generate a Buffer that is a flattened version of this buffer.
  
  Returns
  -------
  flattened : Buffer
      The corresponding flat buffer.
docstr_tok: ["Generate","a","Buffer","that","is","a","flattened","version","of","this","buffer",".","Returns","--","--","--","-","flattened",":","Buffer","The","corresponding","flat","buffer","."]
code: def get_flattened_buffer(self):
      """Generate a Buffer that is a flattened version of this buffer.
  
      Returns
      -------
      flattened : Buffer
          The corresponding flat buffer.
      """
      return _ffi_api.BufferGetFlattenedBuffer(self)
  
file_path: tvm/python/tvm/tir/buffer.py
imports: from numbers import Integral
  import tvm._ffi
  from tvm._ffi.base import string_types
  from tvm.ir import PointerType, PrimExpr, PrimType, Range
  from tvm.runtime import Object, Scriptable, convert
  from .None import _ffi_api
label_desc: Use image node_id 5 for calling the Buffer obj's underlying member method code with example usage: obj.get_flattened_buffer() and returns: _ffi_api