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This repository was archived by the owner on Nov 17, 2023. It is now read-only.
import mxnet as mx
import numpy as np
a = mx.sym.Variable('a')
b = mx.sym.transpose(a, axes=(1, 0, 2))
c = mx.sym.zeros_like(b)
mod = c.simple_bind(mx.cpu(), a=(3, 4, 5), grad_req='null')
mod.arg_arrays[0][:] = np.random.normal(size=mod.arg_arrays[0].shape)
out = mod.forward(is_train=False)
print(out[0])
Error message:
mxnet.base.MXNetError: [22:56:12] src/operator/tensor/./matrix_op-inl.h:328: Check failed: req[0] == kWriteTo (0 vs. 1) : Transpose does not support inplace
Environment info (Required)
Package used (Python/R/Scala/Julia):
Python
Reproduce:
pip install mxnet and run the demo case above.