import unittest import hypothesis.strategies as st from hypothesis import given 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 ExpandDimsSqueezeTest(hu.HypothesisTestCase): @given( squeeze_dims=st.lists(st.integers(0, 3), min_size=1, max_size=3), inplace=st.booleans(), **mu.gcs ) def test_squeeze(self, squeeze_dims, inplace, gc, dc): shape = [ 1 if dim in squeeze_dims else np.random.randint(1, 5) for dim in range(4) ] X = np.random.rand(*shape).astype(np.float32) op = core.CreateOperator( "Squeeze", "X", "X" if inplace else "Y", dims=squeeze_dims ) self.assertDeviceChecks(dc, op, [X], [0]) @given( squeeze_dims=st.lists(st.integers(0, 3), min_size=1, max_size=3), inplace=st.booleans(), **mu.gcs_cpu_ideep ) def test_squeeze_fallback(self, squeeze_dims, inplace, gc, dc): shape = [ 1 if dim in squeeze_dims else np.random.randint(1, 5) for dim in range(4) ] X = np.random.rand(*shape).astype(np.float32) op0 = core.CreateOperator( "Squeeze", "X0", "X0" if inplace else "Y0", dims=squeeze_dims, device_option=dc[0] ) workspace.FeedBlob('X0', X, dc[0]) workspace.RunOperatorOnce(op0) Y0 = workspace.FetchBlob("X0" if inplace else "Y0") op1 = core.CreateOperator( "Squeeze", "X1", "X1" if inplace else "Y1", dims=squeeze_dims, device_option=dc[1] ) workspace.FeedBlob('X1', X, dc[0]) workspace.RunOperatorOnce(op1) Y1 = workspace.FetchBlob("X1" if inplace else "Y1") if not np.allclose(Y0, Y1, atol=0.01, rtol=0.01): print(Y1.flatten()) print(Y0.flatten()) print(np.max(np.abs(Y1 - Y0))) self.assertTrue(False) @given( squeeze_dims=st.lists(st.integers(0, 3), min_size=1, max_size=3), inplace=st.booleans(), **mu.gcs ) def test_expand_dims(self, squeeze_dims, inplace, gc, dc): oshape = [ 1 if dim in squeeze_dims else np.random.randint(2, 5) for dim in range(4) ] nshape = [s for s in oshape if s!=1] expand_dims = [i for i in range(len(oshape)) if oshape[i]==1] X = np.random.rand(*nshape).astype(np.float32) op = core.CreateOperator( "ExpandDims", "X", "X" if inplace else "Y", dims=expand_dims ) self.assertDeviceChecks(dc, op, [X], [0]) @given( squeeze_dims=st.lists(st.integers(0, 3), min_size=1, max_size=3), inplace=st.booleans(), **mu.gcs_cpu_ideep ) def test_expand_dims_fallback(self, squeeze_dims, inplace, gc, dc): oshape = [ 1 if dim in squeeze_dims else np.random.randint(2, 5) for dim in range(4) ] nshape = [s for s in oshape if s!=1] expand_dims = [i for i in range(len(oshape)) if oshape[i]==1] X = np.random.rand(*nshape).astype(np.float32) op0 = core.CreateOperator( "ExpandDims", "X0", "X0" if inplace else "Y0", dims=expand_dims, device_option=dc[0] ) workspace.FeedBlob('X0', X, dc[0]) workspace.RunOperatorOnce(op0) Y0 = workspace.FetchBlob("X0" if inplace else "Y0") op1 = core.CreateOperator( "ExpandDims", "X1", "X1" if inplace else "Y1", dims=expand_dims, device_option=dc[1] ) workspace.FeedBlob('X1', X, dc[0]) workspace.RunOperatorOnce(op1) Y1 = workspace.FetchBlob("X1" if inplace else "Y1") if not np.allclose(Y0, Y1, atol=0.01, rtol=0.01): print(Y1.flatten()) print(Y0.flatten()) print(np.max(np.abs(Y1 - Y0))) self.assertTrue(False) if __name__ == "__main__": unittest.main()