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/transpose_op_test.py (1284B)

@unittest.skipIf(not workspace.C.use_mkldnn, "No MKLDNN support.")
class TransposeTest(hu.HypothesisTestCase):
    @given(
        X=hu.tensor(min_dim=1, max_dim=5, dtype=np.float32), use_axes=st.booleans(), **mu.gcs)
    @settings(deadline=None, max_examples=50)
    def test_transpose(self, X, use_axes, gc, dc):
        ndim = len(X.shape)
        axes = np.arange(ndim)
        np.random.shuffle(axes)

if use_axes:
            op = core.CreateOperator(
                "Transpose", ["X"], ["Y"], axes=axes, device_option=gc)
        else:
            op = core.CreateOperator(
                "Transpose", ["X"], ["Y"], device_option=gc)

def transpose_ref(X):
            if use_axes:
                return [np.transpose(X, axes=axes)]
            else:
                return [np.transpose(X)]

self.assertReferenceChecks(gc, op, [X], transpose_ref)
        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 TransposeTest(hu.HypothesisTestCase): @given( X=hu.tensor(min_dim=1, max_dim=5, dtype=np.float32), use_axes=st.booleans(), **mu.gcs) @settings(deadline=None, max_examples=50) def test_transpose(self, X, use_axes, gc, dc): ndim = len(X.shape) axes = np.arange(ndim) np.random.shuffle(axes) if use_axes: op = core.CreateOperator( "Transpose", ["X"], ["Y"], axes=axes, device_option=gc) else: op = core.CreateOperator( "Transpose", ["X"], ["Y"], device_option=gc) def transpose_ref(X): if use_axes: return [np.transpose(X, axes=axes)] else: return [np.transpose(X)] self.assertReferenceChecks(gc, op, [X], transpose_ref) self.assertDeviceChecks(dc, op, [X], [0]) self.assertGradientChecks(gc, op, [X], 0, [0]) if __name__ == "__main__": unittest.main()