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Support getitem by ellipsis index in dynamic mode #34267

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merged 4 commits into from
Jul 22, 2021
Merged

Support getitem by ellipsis index in dynamic mode #34267

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4eba782
Support getitem by ellipsis index in dynamic mode
zyfncg Jul 20, 2021
48414a7
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
zyfncg Jul 20, 2021
db60dc2
change some code style
zyfncg Jul 21, 2021
0fe6bcb
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
zyfncg Jul 21, 2021
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37 changes: 27 additions & 10 deletions paddle/fluid/pybind/imperative.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -432,19 +432,31 @@ static void ParseIndexingSlice(framework::LoDTensor *tensor, PyObject *_index,
const auto &shape = tensor->dims();
const int rank = shape.size();
const int size = PyTuple_GET_SIZE(index);

// specified_dims is the number of dimensions which indexed by Interger,
// Slices.
int specified_dims = 0;
for (int dim = 0; dim < size; ++dim) {
PyObject *slice_item = PyTuple_GetItem(index, dim);
if (PyCheckInteger(slice_item) || PySlice_Check(slice_item)) {
specified_dims++;
}
}

PADDLE_ENFORCE_EQ(
size <= rank, true,
platform::errors::InvalidArgument(
"too many indices (%d) for tensor of dimension %d", size, rank));
for (int dim = 0; dim < size; ++dim) {
PyObject *slice_item = PyTuple_GetItem(index, dim);
PADDLE_ENFORCE_EQ(PyCheckInteger(slice_item) || PySlice_Check(slice_item),
true,
platform::errors::InvalidArgument(
"Currently, VarBase.__getitem__() only allows "
"indexing by Integers, Slices, and tuples of "
"these types, but received %s in %dth slice item",
std::string(Py_TYPE(slice_item)->tp_name), dim + 1));
for (int i = 0, dim = 0; i < size; ++i) {
PyObject *slice_item = PyTuple_GetItem(index, i);
PADDLE_ENFORCE_EQ(
PyCheckInteger(slice_item) || PySlice_Check(slice_item) ||
slice_item == Py_Ellipsis,
true, platform::errors::InvalidArgument(
"Currently, VarBase.__getitem__() only allows "
"indexing by Integers, Slices, Ellipsis, and tuples of "
"these types, but received %s in %dth slice item",
std::string(Py_TYPE(slice_item)->tp_name), i + 1));
infer_flags->push_back(1);
int dim_len = shape[dim];
if (PyCheckInteger(slice_item)) {
Expand All @@ -467,20 +479,25 @@ static void ParseIndexingSlice(framework::LoDTensor *tensor, PyObject *_index,
slice_ends->push_back(start + 1);
slice_strides->push_back(1);
decrease_axis->push_back(dim);
} else {
dim++;
} else if (PySlice_Check(slice_item)) {
// slice item
Py_ssize_t start, end, step;
PySliceObject *p = reinterpret_cast<PySliceObject *>(slice_item);
_PySlice_GetIndices(p, dim_len, &start, &end, &step);

// :: or : or 0:dim_len:1
if (start == 0 && end == dim_len && step == 1) {
dim++;
continue;
}
slice_axes->push_back(dim);
slice_starts->push_back(start);
slice_ends->push_back(end);
slice_strides->push_back(step);
dim++;
} else if (slice_item == Py_Ellipsis) {
dim += rank - specified_dims;
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@chenwhql chenwhql Jul 21, 2021 •
edited
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may be adding else branch is better, we can move the error hint into else branch, such as

} else {
    PADDLE_THROW(
        platform::errors::InvalidArgument(
                  "Currently, VarBase.__getitem__() only allows "
                  "indexing by Integers, Slices, Ellipsis, and tuples of "
                  "these types, but received %s in %dth slice item",
                  std::string(Py_TYPE(slice_item)->tp_name), i + 1));
}

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Done!

}
}
if (!PyTuple_Check(_index)) Py_DecRef(index);
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54 changes: 54 additions & 0 deletions python/paddle/fluid/tests/unittests/test_var_base.py
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Expand Up @@ -652,6 +652,59 @@ def _test_slice_for_tensor_attr(self):
np.array_equal(local_out[15], tensor_array[::-1, ::-1, ::-1]))
self.assertTrue(np.array_equal(local_out[16], tensor_array[-4:4]))

def _test_for_getitem_ellipsis_index(self):
shape = (64, 3, 5, 256)
np_fp32_value = np.random.random(shape).astype('float32')
np_int_value = np.random.randint(1, 100, shape)

var_fp32 = paddle.to_tensor(np_fp32_value)
var_int = paddle.to_tensor(np_int_value)

# test for float32
var = [
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duplicate code? put the duplicate code in another func?

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Done!

var_fp32[..., 0].numpy(),
var_fp32[..., 1, 0].numpy(),
var_fp32[0, ..., 1, 0].numpy(),
var_fp32[1, ..., 1].numpy(),
var_fp32[2, ...].numpy(),
var_fp32[2, 0, ...].numpy(),
var_fp32[2, 0, 1, ...].numpy(),
var_fp32[...].numpy(),
var_fp32[:, ..., 100].numpy(),
]

self.assertTrue(np.array_equal(var[0], np_fp32_value[..., 0]))
self.assertTrue(np.array_equal(var[1], np_fp32_value[..., 1, 0]))
self.assertTrue(np.array_equal(var[2], np_fp32_value[0, ..., 1, 0]))
self.assertTrue(np.array_equal(var[3], np_fp32_value[1, ..., 1]))
self.assertTrue(np.array_equal(var[4], np_fp32_value[2, ...]))
self.assertTrue(np.array_equal(var[5], np_fp32_value[2, 0, ...]))
self.assertTrue(np.array_equal(var[6], np_fp32_value[2, 0, 1, ...]))
self.assertTrue(np.array_equal(var[7], np_fp32_value[...]))
self.assertTrue(np.array_equal(var[8], np_fp32_value[:, ..., 100]))

# test for int type
var = [
var_int[..., 0].numpy(),
var_int[..., 1, 0].numpy(),
var_int[0, ..., 1, 0].numpy(),
var_int[1, ..., 1].numpy(),
var_int[2, ...].numpy(),
var_int[2, 0, ...].numpy(),
var_int[2, 0, 1, ...].numpy(),
var_int[...].numpy(),
var_int[:, ..., 100].numpy(),
]
self.assertTrue(np.array_equal(var[0], np_int_value[..., 0]))
self.assertTrue(np.array_equal(var[1], np_int_value[..., 1, 0]))
self.assertTrue(np.array_equal(var[2], np_int_value[0, ..., 1, 0]))
self.assertTrue(np.array_equal(var[3], np_int_value[1, ..., 1]))
self.assertTrue(np.array_equal(var[4], np_int_value[2, ...]))
self.assertTrue(np.array_equal(var[5], np_int_value[2, 0, ...]))
self.assertTrue(np.array_equal(var[6], np_int_value[2, 0, 1, ...]))
self.assertTrue(np.array_equal(var[7], np_int_value[...]))
self.assertTrue(np.array_equal(var[8], np_int_value[:, ..., 100]))

def _test_for_var(self):
np_value = np.random.random((30, 100, 100)).astype('float32')
w = fluid.dygraph.to_variable(np_value)
Expand All @@ -664,6 +717,7 @@ def test_slice(self):
self._test_slice()
self._test_slice_for_tensor_attr()
self._test_for_var()
self._test_for_getitem_ellipsis_index()

var = fluid.dygraph.to_variable(self.array)
self.assertTrue(np.array_equal(var[1, :].numpy(), self.array[1, :]))
Expand Down