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()