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/order_switch_op_test.py (2299B)

import unittest
import numpy as np
import hypothesis.strategies as st
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.ideep_test_util as mu

from hypothesis import given, settings
from caffe2.python import core, workspace

@unittest.skipIf(not workspace.C.use_mkldnn, "No MKLDNN support.")
class OrderSwitchTest(hu.HypothesisTestCase):
    @given(n=st.integers(1, 128),
           c=st.integers(1, 64),
           h=st.integers(1, 128),
           w=st.integers(1, 128),
           **mu.gcs)
    @settings(max_examples=10, deadline=None)
    def test_nchw2nhwc(self, n, c, h, w, gc, dc):
        op = core.CreateOperator(
            "NCHW2NHWC",
            ["X"],
            ["Y"],
        )
        X = np.random.rand(n, c, h, w).astype(np.float32) - 0.5

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

@given(n=st.integers(1, 128),
           c=st.integers(1, 64),
           h=st.integers(1, 128),
           w=st.integers(1, 128),
           **mu.gcs)
    @settings(deadline=None, max_examples=50)
    def test_nhwc2nchw(self, n, c, h, w, gc, dc):
        op0 = core.CreateOperator(
            "NCHW2NHWC",
            ["X"],
            ["Y"],
        )
        op1 = core.CreateOperator(
            "NHWC2NCHW",
            ["Y"],
            ["Z"],
        )

X = np.random.rand(n, c, h, w).astype(np.float32) - 0.5

old_ws_name = workspace.CurrentWorkspace()
        workspace.SwitchWorkspace("_device_check_", True)
        workspace.FeedBlob('X', X, dc[0])
        op0.device_option.CopyFrom(dc[0])
        op1.device_option.CopyFrom(dc[0])
        workspace.RunOperatorOnce(op0)
        workspace.RunOperatorOnce(op1)
        Z0 = workspace.FetchBlob("Z")

workspace.ResetWorkspace()
        workspace.FeedBlob('X', X, dc[1])
        op0.device_option.CopyFrom(dc[1])
        op1.device_option.CopyFrom(dc[1])
        workspace.RunOperatorOnce(op0)
        workspace.RunOperatorOnce(op1)
        Z1 = workspace.FetchBlob("Z")

if not np.allclose(Z0, Z1, atol=0.01, rtol=0.01):
            print(Z1.flatten())
            print(Z0.flatten())
            print(np.max(np.abs(Z1 - Z0)))
            self.assertTrue(False)

workspace.SwitchWorkspace(old_ws_name)

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

cmd: