"""NNVM compiler toolchain. User only need to use :any:`build` and :any:`build_config` to do the compilation, and :any:`save_param_dict` to save the parameters into bytes. The other APIs are for more advanced interaction with the compiler toolchain. """ from __future__ import absolute_import import tvm from . import build_module from . build_module import build, optimize, build_config from . compile_engine import engine, graph_key from . param_dict import save_param_dict, load_param_dict from .. import symbol as _symbol from .. import graph as _graph from .. import top as _top tvm.register_extension(_symbol.Symbol, _symbol.Symbol) tvm.register_extension(_graph.Graph, _graph.Graph)
def get_bool(self, key):
"""Get bool from attr dict
Parameters
----------
key : str
The attr key
Returns
-------
value : bool
The result value
"""
lowercase = self[key].lower()
if lowercase == "1":
return True
elif lowercase == "0":
return False
elif lowercase == "true":
return True
elif lowercase == "false":
return False
else:
raise ValueError("Wrong bool format for key %s" % key)
def __repr__(self):
return str({k : self[k] for k in self.keys()})
tvm.register_extension(AttrDict, AttrDict)
if lowercase == "1":
return True
if lowercase == "0":
return False
if lowercase == "true":
return True
if lowercase == "false":
return False
raise ValueError("Wrong bool format for key %s" % key)
def get_str(self, key):
"""Get string from attr dict
Parameters
----------
key : str
The attr key
Returns
-------
value : str
The result value
"""
return self[key]
def __repr__(self):
return str({k: self[k] for k in self.keys()})
tvm.register_extension(AttrDict, AttrDict)
def __del__(self):
# You can also call your own customized
# deleter if you can free it via your own FFI.
tvm.nd.free_extension_handle(self.handle, self.__class__._tvm_tcode)
@property
def _tvm_handle(self):
return self.handle.value
def __getitem__(self, idx):
return ivec_get(self, idx)
# Register IntVec extension on python side.
tvm.register_extension(IntVec, IntVec)
nd_create = tvm.get_global_func("tvm_ext.nd_create")
nd_add_two = tvm.get_global_func("tvm_ext.nd_add_two")
nd_get_addtional_info = tvm.get_global_func("tvm_ext.nd_get_addtional_info")
class NDSubClass(tvm.nd.NDArrayBase):
"""Example for subclassing TVM's NDArray infrastructure.
By inheriting TMV's NDArray, external libraries could
leverage TVM's FFI without any modification.
"""
# Should be consistent with the type-trait set in the backend
_array_type_code = 1
def __init__(self, handle):
self.handle = handle
def __del__(self):
_tvm.nd.free_extension_handle(self.handle, 27)
@property
def _tvm_handle(self):
return self.handle.value
def __getitem__(self, idx):
return ivec_get(self, idx)
_tvm.register_extension(IntVector, IntVector)
class Target(object):
"""Handle to C++ Target instance """
_tvm_tcode = 28
def __init__(self, handle):
self.handle = handle
def __del__(self):
_tvm.nd.free_extension_handle(self.handle, 28)
@property
def _tvm_handle(self):
return self.handle.value
# Expose two functions into python
bind_add = tvm.get_global_func("tvm_ext.bind_add")
sym_add = tvm.get_global_func("tvm_ext.sym_add")
ivec_create = tvm.get_global_func("tvm_ext.ivec_create")
ivec_get = tvm.get_global_func("tvm_ext.ivec_get")
class IntVec(object):
"""Example for using extension class in c++ """
_tvm_tcode = 17
def __init__(self, handle):
self.handle = handle
def __del__(self):
# You can also call your own customized
# deleter if you can free it via your own FFI.
tvm.nd.free_extension_handle(self.handle, 17)
@property
def _tvm_handle(self):
return self.handle.value
def __getitem__(self, idx):
return ivec_get(self, idx)
# Register IntVec extension on python side.
tvm.register_extension(IntVec, IntVec)
self.handle = handle
def __del__(self):
# You can also call your own customized
# deleter if you can free it via your own FFI.
tvm.nd.free_extension_handle(self.handle, self.__class__._tvm_tcode)
@property
def _tvm_handle(self):
return self.handle.value
def __getitem__(self, idx):
return ivec_get(self, idx)
# Register IntVec extension on python side.
tvm.register_extension(IntVec, IntVec)
nd_create = tvm.get_global_func("tvm_ext.nd_create")
nd_add_two = tvm.get_global_func("tvm_ext.nd_add_two")
nd_get_addtional_info = tvm.get_global_func("tvm_ext.nd_get_addtional_info")
class NDSubClass(tvm.nd.NDArrayBase):
"""Example for subclassing TVM's NDArray infrastructure.
By inheriting TMV's NDArray, external libraries could
leverage TVM's FFI without any modification.
"""
# Should be consistent with the type-trait set in the backend
_array_type_code = 1
_LIB = load_lib()
# Expose two functions into python
bind_add = tvm.get_global_func("tvm_ext.bind_add")
sym_add = tvm.get_global_func("tvm_ext.sym_add")
ivec_create = tvm.get_global_func("tvm_ext.ivec_create")
ivec_get = tvm.get_global_func("tvm_ext.ivec_get")
class IntVec(object):
"""Example for using extension class in c++ """
_tvm_tcode = 17
def __init__(self, handle):
self.handle = handle
def __del__(self):
# You can also call your own customized
# deleter if you can free it via your own FFI.
tvm.nd.free_extension_handle(self.handle, 17)
@property
def _tvm_handle(self):
return self.handle.value
def __getitem__(self, idx):
return ivec_get(self, idx)
# Register IntVec extension on python side.
tvm.register_extension(IntVec, IntVec)
