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- from copy import deepcopy
-
- from .. import functional as F
- from ..core import _config
- from ..module import Module
- from ..tensor import Tensor
-
-
- def _is_nchw_format(param: Tensor):
- # TODO: use better condition
- return (param.ndim == 4 or param.ndim == 5) and param.format != "nhwc"
-
-
- def convert_tensor_format(x: Tensor, inplace: bool = True):
- """Convert NCHW Tensor to NHWC Tensor."""
- if not _is_nchw_format(x):
- return x
-
- if x.ndim != 4 and x.ndim != 5:
- raise ValueError("Unsupport tensor ndim {}".format(x.ndim))
- if x.format != "nhwc":
- # hostvalue should still be valid, so no d2h cost.
- data = x.numpy()
- if inplace:
- # reset will destroy existed backward grad
- x[...] = Tensor(data, format="nhwc")
- else:
- # use mge interface to maintain grad
- x = Tensor(data, format="nhwc")
- return x
-
-
- def convert_module_format(module: Module, inplace: bool = True):
- """Convert NCHW Module to NHWC Module."""
- if not inplace:
- module = deepcopy(module)
-
- for name, param in module.named_tensors():
- convert_tensor_format(param, inplace=True)
- return module
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