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/dropout_op_test.py (2075B)

@unittest.skipIf(not workspace.C.use_mkldnn, "No MKLDNN support.")
class DropoutTest(hu.HypothesisTestCase):

@given(X=hu.tensor(),
           in_place=st.booleans(),
           ratio=st.floats(0, 0.999),
           **mu.gcs)
    def test_dropout_is_test(self, X, in_place, ratio, gc, dc):
        """Test with is_test=True for a deterministic reference impl."""
        op = core.CreateOperator('Dropout', ['X'],
                                 ['X' if in_place else 'Y'],
                                 ratio=ratio, is_test=True)

self.assertDeviceChecks(dc, op, [X], [0])
        # No sense in checking gradients for test phase

def reference_dropout_test(x):
            return x, np.ones(x.shape, dtype=np.bool)
        self.assertReferenceChecks(
            gc, op, [X], reference_dropout_test,
            # The 'mask' output may be uninitialized
            outputs_to_check=[0])

@given(X=hu.tensor(),
           in_place=st.booleans(),
           output_mask=st.booleans(),
           **mu.gcs)
    @unittest.skipIf(True, "Skip duo to different rand seed.")
    def test_dropout_ratio0(self, X, in_place, output_mask, gc, dc):
        """Test with ratio=0 for a deterministic reference impl."""
        is_test = not output_mask
        op = core.CreateOperator('Dropout', ['X'],
                                 ['X' if in_place else 'Y'] +
                                 (['mask'] if output_mask else []),
                                 ratio=0.0, is_test=is_test)

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

def reference_dropout_ratio0(x):
            return (x,) if is_test else (x, np.ones(x.shape, dtype=np.bool))
        self.assertReferenceChecks(
            gc, op, [X], reference_dropout_ratio0, outputs_to_check=[0])

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

import unittest from hypothesis import given import hypothesis.strategies as st 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 DropoutTest(hu.HypothesisTestCase): @given(X=hu.tensor(), in_place=st.booleans(), ratio=st.floats(0, 0.999), **mu.gcs) def test_dropout_is_test(self, X, in_place, ratio, gc, dc): """Test with is_test=True for a deterministic reference impl.""" op = core.CreateOperator('Dropout', ['X'], ['X' if in_place else 'Y'], ratio=ratio, is_test=True) self.assertDeviceChecks(dc, op, [X], [0]) # No sense in checking gradients for test phase def reference_dropout_test(x): return x, np.ones(x.shape, dtype=np.bool) self.assertReferenceChecks( gc, op, [X], reference_dropout_test, # The 'mask' output may be uninitialized outputs_to_check=[0]) @given(X=hu.tensor(), in_place=st.booleans(), output_mask=st.booleans(), **mu.gcs) @unittest.skipIf(True, "Skip duo to different rand seed.") def test_dropout_ratio0(self, X, in_place, output_mask, gc, dc): """Test with ratio=0 for a deterministic reference impl.""" is_test = not output_mask op = core.CreateOperator('Dropout', ['X'], ['X' if in_place else 'Y'] + (['mask'] if output_mask else []), ratio=0.0, is_test=is_test) self.assertDeviceChecks(dc, op, [X], [0]) def reference_dropout_ratio0(x): return (x,) if is_test else (x, np.ones(x.shape, dtype=np.bool)) self.assertReferenceChecks( gc, op, [X], reference_dropout_ratio0, outputs_to_check=[0]) if __name__ == "__main__": unittest.main()