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| 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() |
|
|
