vandanavk commented on a change in pull request #14035: [WIP] Fix documentation
for bilinear upsampling and add unit test
URL: https://github.com/apache/incubator-mxnet/pull/14035#discussion_r258125213
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File path: tests/python/unittest/test_operator.py
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@@ -1491,17 +1491,30 @@ def check_nearest_upsampling_with_shape(shapes, scale,
root_scale):
assert_allclose(arr[name].asnumpy()*root_scale**2*scale**(2*k),
arr_grad[name].asnumpy(), rtol=1e-4)
-def check_bilinear_upsampling_with_shape(shapes, scale, root_scale):
- arr = {'arg_%d'%i: mx.random.uniform(-10.0, 10.0, shape,
ctx=mx.cpu()).copyto(default_context()) for i, shape in zip(range(len(shapes)),
shapes)}
- arr_grad = {'arg_%d'%i: mx.nd.zeros(shape) for i, shape in
zip(range(len(shapes)), shapes)}
-
- up = mx.sym.UpSampling(*[mx.sym.Variable('arg_%d'%i) for i in
range(len(shapes))], sample_type='bilinear', scale=root_scale)
+def check_bilinear_upsampling_with_shape(data_shape, weight_shape, scale,
root_scale, num_filter):
Review comment:
@apeforest the unit test was not being called previously. And based on
inputs from the issues in Ref section of the PR description, many users are
confused about how to use the Upsampling operator with the bilinear upsampling
option. So i thought I could add/modify tests here as well - which would show
how to use the operator.
I have updated the PR title - should I open a separate PR instead?
Note: This PR is WIP as an assert has to be added at the end of the test.
Based on an offline discussion with @anirudh2290 yesterday, the assert will be
similar to what was done for test_deconvolution()
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