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import numpy as np
from caffe2.python import core, workspace
from caffe2.python.test_util import TestCase
class TestSplitOpCost(TestCase):
def _verify_cost(self, workspace, split_op):
flops, bytes_written, bytes_read = workspace.GetOperatorCost(
split_op, split_op.input
)
self.assertEqual(flops, 0)
self.assertEqual(
bytes_read,
sum(workspace.FetchBlob(b).nbytes for b in split_op.input),
)
self.assertEqual(
bytes_written,
sum(workspace.FetchBlob(b).nbytes for b in split_op.output),
)
def test_columnwise_equal_outputSplit(self):
workspace.ResetWorkspace()
workspace.FeedBlob("input", np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int32))
split_op = core.CreateOperator(
"Split",
["input"],
["output_1", "output_2", "output_3"],
)
workspace.RunOperatorOnce(split_op)
output_1 = workspace.FetchBlob("output_1")
self.assertTupleEqual(output_1.shape, (2, 1))
np.testing.assert_array_equal(output_1, [[1], [4]])
output_2 = workspace.FetchBlob("output_2")
np.testing.assert_array_equal(output_2, [[2], [5]])
output_3 = workspace.FetchBlob("output_3")
np.testing.assert_array_equal(output_3, [[3], [6]])
self._verify_cost(workspace, split_op)
def test_rowwise_equal_outputSplit(self):
workspace.ResetWorkspace()
workspace.FeedBlob("input", np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int32))
split_op = core.CreateOperator(
"Split",
["input"],
["output_1", "output_2"],
axis=0,
)
workspace.RunOperatorOnce(split_op)
output_1 = workspace.FetchBlob("output_1")
self.assertTupleEqual(output_1.shape, (1, 3))
np.testing.assert_array_equal(output_1, [[1, 2, 3]])
output_2 = workspace.FetchBlob("output_2")
np.testing.assert_array_equal(output_2, [[4, 5, 6]])
self._verify_cost(workspace, split_op)
def test_columnwise_equal_outputSplit_columnRemoved(self):
workspace.ResetWorkspace()
workspace.FeedBlob("input", np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int32))
# To be able to use 'add_axis' (which should have been called 'remove_axis') on 'axis',
# the dimensions of split tensors must match on 'axis'
split_op = core.CreateOperator(
"Split",
["input"],
["output_1", "output_2", "output_3"],
axis=1,
add_axis=1,
)
workspace.RunOperatorOnce(split_op)
output_1 = workspace.FetchBlob("output_1")
self.assertTupleEqual(output_1.shape, (2,))
np.testing.assert_array_equal(output_1, [1, 4])
output_2 = workspace.FetchBlob("output_2")
np.testing.assert_array_equal(output_2, [2, 5])
output_3 = workspace.FetchBlob("output_3")
np.testing.assert_array_equal(output_3, [3, 6])
self._verify_cost(workspace, split_op)
def test_rowwise_equal_outputSplit_rowRemoved(self):
workspace.ResetWorkspace()
workspace.FeedBlob("input", np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int32))
split_op = core.CreateOperator(
"Split",
["input"],
["output_1", "output_2"],
axis=0,
add_axis=1,
)
workspace.RunOperatorOnce(split_op)
output_1 = workspace.FetchBlob("output_1")
self.assertTupleEqual(output_1.shape, (3,))
np.testing.assert_array_equal(output_1, [1, 2, 3])
output_2 = workspace.FetchBlob("output_2")
np.testing.assert_array_equal(output_2, [4, 5, 6])
self._verify_cost(workspace, split_op)
def test_rowwise_unequal_argSplit(self):
workspace.ResetWorkspace()
workspace.FeedBlob(
"input", np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=np.int32)
)
split_op = core.CreateOperator(
"Split",
["input"],
["output_1", "output_2"],
axis=0,
split=[1, 2],
)
workspace.RunOperatorOnce(split_op)
output_1 = workspace.FetchBlob("output_1")
self.assertTupleEqual(output_1.shape, (1, 3))
np.testing.assert_array_equal(output_1, [[1, 2, 3]])
output_2 = workspace.FetchBlob("output_2")
self.assertTupleEqual(output_2.shape, (2, 3))
np.testing.assert_array_equal(output_2, [[4, 5, 6], [7, 8, 9]])
self._verify_cost(workspace, split_op)
def test_rowwise_unequal_argSplit_rowRemoved(self):
workspace.ResetWorkspace()
workspace.FeedBlob(
"input", np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=np.int32)
)
split_op = core.CreateOperator(
"Split",
["input"],
["output_1", "output_2", "output_3"],
axis=0,
split=[1, 1, 1],
add_axis=1,
)
workspace.RunOperatorOnce(split_op)
output_1 = workspace.FetchBlob("output_1")
self.assertTupleEqual(output_1.shape, (3,))
np.testing.assert_array_equal(output_1, [1, 2, 3])
output_2 = workspace.FetchBlob("output_2")
np.testing.assert_array_equal(output_2, [4, 5, 6])
output_3 = workspace.FetchBlob("output_3")
np.testing.assert_array_equal(output_3, [7, 8, 9])
self._verify_cost(workspace, split_op)
def test_rowwise_unequal_blobSplit(self):
workspace.ResetWorkspace()
workspace.FeedBlob(
"input", np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=np.int32)
)
workspace.FeedBlob("split", np.array([1, 2], dtype=np.int32))
split_op = core.CreateOperator(
"Split",
["input", "split"],
["output_1", "output_2"],
axis=0,
)
workspace.RunOperatorOnce(split_op)
output_1 = workspace.FetchBlob("output_1")
self.assertTupleEqual(output_1.shape, (1, 3))
np.testing.assert_array_equal(output_1, [[1, 2, 3]])
output_2 = workspace.FetchBlob("output_2")
self.assertTupleEqual(output_2.shape, (2, 3))
np.testing.assert_array_equal(output_2, [[4, 5, 6], [7, 8, 9]])
self._verify_cost(workspace, split_op)
def test_columnwise_unequal_argSplit(self):
workspace.ResetWorkspace()
workspace.FeedBlob("input", np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int32))
split_op = core.CreateOperator(
"Split",
["input"],
["output_1", "output_2"],
axis=1,
split=[1, 2],
)
workspace.RunOperatorOnce(split_op)
output_1 = workspace.FetchBlob("output_1")
self.assertTupleEqual(output_1.shape, (2, 1))
np.testing.assert_array_equal(output_1, [[1], [4]])
output_2 = workspace.FetchBlob("output_2")
self.assertTupleEqual(output_2.shape, (2, 2))
np.testing.assert_array_equal(output_2, [[2, 3], [5, 6]])
self._verify_cost(workspace, split_op)
def test_columnWise_unequal_blobSplit_columnRemoved(self):
workspace.ResetWorkspace()
workspace.FeedBlob("input", np.array([[1, 2, 3], [4, 5, 6]], dtype=np.int32))
workspace.FeedBlob("split", np.array([1, 1, 1], dtype=np.int32))
split_op = core.CreateOperator(
"Split",
["input", "split"],
["output_1", "output_2", "output_3"],
axis=1,
add_axis=1,
)
workspace.RunOperatorOnce(split_op)
output_1 = workspace.FetchBlob("output_1")
self.assertTupleEqual(output_1.shape, (2,))
np.testing.assert_array_equal(output_1, [1, 4])
output_2 = workspace.FetchBlob("output_2")
np.testing.assert_array_equal(output_2, [2, 5])
output_3 = workspace.FetchBlob("output_3")
np.testing.assert_array_equal(output_3, [3, 6])
self._verify_cost(workspace, split_op)
def test_equal_outputSplit_NHWC(self):
workspace.ResetWorkspace()
workspace.FeedBlob("input", np.random.rand(2, 5, 7, 9).astype(np.int32))
split_op = core.CreateOperator(
"Split",
["input"],
["output_1", "output_2", "output_3"],
order="NHWC",
)
workspace.RunOperatorOnce(split_op)
for b in split_op.output:
self.assertTupleEqual(workspace.FetchBlob(b).shape, (2, 5, 7, 3))
self._verify_cost(workspace, split_op)
|
