# -*- coding: utf-8 -*-
# pylint: disable=redefined-builtin
from typing import Iterable, List, Sequence
from ..core._imperative_rt.core2 import apply
from ..core.ops import builtin
[文档]def extern_opr_subgraph(
inputs, output_shapes: List[tuple], dump_name: str, dump_data: bytes, output_dtypes
):
r"""Load a serialized extern opr subgraph and fake execute the operator.
Args:
inputs: list of input tensors.
output_shapes: The output shapes.
dump_name: The serialized subgraph name.
dump_data: The serialized subgraph.
"""
if not isinstance(inputs, Iterable):
inputs = (inputs,)
op = builtin.ExternOpr(
output_shapes, dump_name, dump_data, len(dump_data), output_dtypes
)
return apply(op, *inputs)
[文档]def tensorrt_runtime_opr(inputs, *, data: bytes = None):
# empty model will give None result
if data is None:
return None
op = builtin.TensorRTRuntime(data, len(data))
# return sequence of outputs
return apply(op, *inputs)
[文档]def cambricon_runtime_opr(inputs, data, symbol, tensor_dim_mutable):
r"""Load a serialized Cambricon model as a runtime operator in MegEngine.
Args:
inputs: list of input tensors.
data: the serialized Cambricon model.
symbol: name of the function in Cambricon model.
tensor_dim_mutable: whether the input tensors' shapes are mutable
in ``cnrtModel_t``.
"""
op = builtin.CambriconRuntime(data, len(data), symbol, tensor_dim_mutable)
return apply(op, *inputs)
[文档]def atlas_runtime_opr(inputs, data):
r"""Load a serialized Atlas model as a runtime operator in MegEngine.
Args:
inputs: list of input tensors.
data: the serialized Atlas model.
"""
op = builtin.AtlasRuntime(data, len(data))
return apply(op, *inputs)
[文档]def magicmind_runtime_opr(inputs, data):
r"""Load a serialized MagicMind model as a runtime operator in MegEngine.
Args:
inputs: list of input tensors.
data: the serialized MagicMind model.
"""
op = builtin.MagicMindRuntime(data, len(data))
return apply(op, *inputs)