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import numpy as np
import mxnet as mx
from mxnet import gluon
from numpy.testing import assert_allclose, assert_array_equal
from mxnet.test_utils import *
from mxnet.base import _as_list
from mxnet.attribute import AttrScope
from common import with_seed
def test_dynamic_shape():
class _TestBlock(gluon.HybridBlock):
def __init__(self):
super(_TestBlock, self).__init__()
def hybrid_forward(self, F, data, index):
return F.contrib.boolean_mask(data, index)
block = _TestBlock()
block.hybridize()
data = mx.nd.array([[1, 2, 3],[4, 5, 6],[7, 8, 9]])
index = mx.nd.array([0, 1, 1])
data.attach_grad()
with mx.autograd.record():
result = block(data, index)
result.backward()
result_nd = np.array([[4, 5, 6], [7, 8, 9]])
data_grad_nd = np.array([[0., 0., 0.], [1., 1., 1.], [1., 1., 1.]])
assert_almost_equal(result.asnumpy(), result_nd)
assert_almost_equal(data.grad.asnumpy(), data_grad_nd)
if __name__ == '__main__':
import nose
nose.runmodule()