marcoabreu commented on a change in pull request #16341: [WIP][New Op] Add
deformable conv v2
URL: https://github.com/apache/incubator-mxnet/pull/16341#discussion_r330663090
##########
File path: tests/python/unittest/test_contrib_operator.py
##########
@@ -333,6 +334,46 @@ def test_multibox_prior_op():
boxes = Y.reshape((h, w, 5, 4))
assert_allclose(boxes.asnumpy()[250, 250, 0, :], np.array([-0.948249,
0.362671, 1.636436, 0.530377]), atol=1e-5, rtol=1e-5)
+@with_seed()
+def test_modulated_deformable_convolution():
+ for num_batch in [1, 2]:
+ for num_channel_data, num_deformable_group in itertools.product([4,
8], [1, 2]):
+ for input_height, input_width in itertools.product([5, 6], [5, 6]):
+ for dilate in [(1, 1), (2, 2)]:
+ for grad_nodes in [['im_data'], ['offset_data'],
['weight']]:
+ output_height = input_height
+ output_width = input_width
+ im_data = np.random.rand(num_batch, num_channel_data,
input_height, input_width)
+ offset_data = \
+ np.random.rand(num_batch, num_deformable_group * 3
* 3 * 2, output_height, output_width)\
+ * 0.8 + 0.1
+ mask_data = np.random.rand(num_batch,
num_deformable_group * 3 * 3, output_height, output_width)
+ mask_data = 0.5 * (1 + np.tanh(0.5 * mask_data)) #
sigmoid
+ weight = np.random.normal(0, 0.001, (num_channel_data,
num_channel_data, 3, 3))
+ bias = np.zeros(num_channel_data)
+
+ im_data_var = mx.symbol.Variable(name="im_data")
+ offset_data_var =
mx.symbol.Variable(name="offset_data")
+ mask_data_var = mx.symbol.Variable(name="mask_data")
+ weight_var = mx.symbol.Variable(name="weight")
+ bias_var = mx.symbol.Variable(name="bias")
+ op =
mx.sym.contrib.ModulatedDeformableConvolution(name='test_op', data=im_data_var,
+
offset=offset_data_var, mask=mask_data_var,
+
weight=weight_var, bias=bias_var,
+
num_filter=num_channel_data, pad=dilate,
+
kernel=(3, 3), stride=(1, 1), dilate=dilate,
+
num_deformable_group=num_deformable_group)
+ if grad_nodes[0] == 'offset_data':
+ # wider tolerance needed for coordinate
differential
+ rtol, atol = 1.0, 1e-2
+ else:
+ rtol, atol = 0.05, 1e-3
+ # By now we only have gpu implementation
+ if default_context().device_type == 'gpu':
Review comment:
Please use conditional test annotations instead of making an exclude inside
the test. Otherwise, we won't know that it has been skipped.
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