FM / ideep

/usr/local/lib64/python3.6/site-packages/caffe2/python/ideep/

/usr/local/lib64/python3.6/site-packages/caffe2/python/ideep

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
adam_op_test.py	3212	0644	edit dl rm
blobs_queue_db_test.py	4045	0644	edit dl rm
channel_shuffle_op_test.py	1286	0644	edit dl rm
concat_split_op_test.py	5532	0644	edit dl rm
convfusion_op_test.py	31919	0644	edit dl rm
conv_op_test.py	5666	0644	edit dl rm
conv_transpose_test.py	2595	0644	edit dl rm
copy_op_test.py	3074	0644	edit dl rm
dropout_op_test.py	2075	0644	edit dl rm
elementwise_sum_op_test.py	6317	0644	edit dl rm
expanddims_squeeze_op_test.py	4285	0644	edit dl rm
fc_op_test.py	11745	0644	edit dl rm
leaky_relu_op_test.py	2854	0644	edit dl rm
LRN_op_test.py	1195	0644	edit dl rm
moment_sgd_op_test.py	1777	0644	edit dl rm
operator_fallback_op_test.py	3450	0644	edit dl rm
order_switch_op_test.py	2299	0644	edit dl rm
pool_op_test.py	4296	0644	edit dl rm
pre_convert_test.py	4115	0644	edit dl rm
relu_op_test.py	3705	0644	edit dl rm
reshape_op_test.py	5919	0644	edit dl rm
shape_op_test.py	2631	0644	edit dl rm
sigmoid_op_test.py	775	0644	edit dl rm
softmax_op_test.py	932	0644	edit dl rm
spatial_bn_op_test.py	5237	0644	edit dl rm
test_ideep_net.py	4094	0644	edit dl rm
transform_ideep_net.py	11683	0644	edit dl rm
transpose_op_test.py	1284	0644	edit dl rm
weightedsum_op_test.py	1560	0644	edit dl rm
__init__.py	0	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/caffe2/python/ideep/channel_shuffle_op_test.py (1286B)

@unittest.skipIf(not workspace.C.use_mkldnn, "No MKLDNN support.")
class ChannelShuffleTest(hu.HypothesisTestCase):
    @given(size=st.integers(8, 10),
           input_channels=st.integers(1, 3),
           batch_size=st.integers(1, 32),
           group=st.integers(2, 4),
           stride=st.integers(1, 3),
           pad=st.integers(0, 3),
           kernel=st.integers(3, 5),
           **mu.gcs)
    @settings(max_examples=10, deadline=None)
    def test_channel_shuffle(self, size, input_channels, batch_size, group, stride, pad, kernel, gc, dc):
        op = core.CreateOperator(
            "ChannelShuffle",
            ["X"],
            ["Y"],
            group=group,
            stride=stride,
            pad=pad,
            kernel=kernel,
        )
        X = np.random.rand(
            batch_size, input_channels * group, size, size).astype(np.float32) - 0.5

self.assertDeviceChecks(dc, op, [X], [0])

self.assertGradientChecks(gc, op, [X], 0, [0])

if __name__ == "__main__":
    unittest.main()

import unittest import hypothesis.strategies as st from hypothesis import given, settings import numpy as np from caffe2.python import core, workspace import caffe2.python.hypothesis_test_util as hu import caffe2.python.ideep_test_util as mu @unittest.skipIf(not workspace.C.use_mkldnn, "No MKLDNN support.") class ChannelShuffleTest(hu.HypothesisTestCase): @given(size=st.integers(8, 10), input_channels=st.integers(1, 3), batch_size=st.integers(1, 32), group=st.integers(2, 4), stride=st.integers(1, 3), pad=st.integers(0, 3), kernel=st.integers(3, 5), **mu.gcs) @settings(max_examples=10, deadline=None) def test_channel_shuffle(self, size, input_channels, batch_size, group, stride, pad, kernel, gc, dc): op = core.CreateOperator( "ChannelShuffle", ["X"], ["Y"], group=group, stride=stride, pad=pad, kernel=kernel, ) X = np.random.rand( batch_size, input_channels * group, size, size).astype(np.float32) - 0.5 self.assertDeviceChecks(dc, op, [X], [0]) self.assertGradientChecks(gc, op, [X], 0, [0]) if __name__ == "__main__": unittest.main()