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Return (-1) if max_int stop/start provided (#9386)

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Katarzyna Mitrus authored and GitHub committed 2021-12-23 16:13:56 +03:00
1 parent 8315fe0e19
commit 3ee5bcaf4d
2 files changed
+96 -11
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src/core/src/op/slice.cpp
+20 -5
View File
@@ -60,6 +60,20 @@ int64_t get_sliced_dim_size(int64_t start, int64_t stop, int64_t step, int64_t d
return sliced_dim_size;
}
bool is_max_int(element::Type_t ind_type, int64_t value) {
int64_t max_type_value = 0;
switch (ind_type) {
case element::i32:
max_type_value = std::numeric_limits<typename element_type_traits<element::i32>::value_type>::max();
break;
case element::i64:
max_type_value = std::numeric_limits<typename element_type_traits<element::i64>::value_type>::max();
break;
default:
return false;
}
return max_type_value == value;
}
} // namespace
bool op::v8::Slice::visit_attributes(AttributeVisitor& visitor) {
@@ -288,16 +302,17 @@ PartialShape op::v8::Slice::calculate_output_shape(const std::vector<int64_t>& s
// Avoid negative index normalization without upper bounds
if (!axis_dim.get_interval().has_upper_bound()) {
if ((step < 0 && start < 0 && stop > 0) || (step > 0 && stop < 0 && start > 0)) {
if (is_max_int(get_input_element_type(2), stop) || is_max_int(get_input_element_type(1), start)) {
output_shape[norm_axis] = Dimension(-1);
continue;
} else if ((step < 0 && start < 0 && stop > 0) || (step > 0 && stop < 0 && start > 0)) {
output_shape[norm_axis] = Dimension(-1);
continue;
} else if (step < 0 && start > 0 && stop < 0) {
int64_t max_out_dim = start >= INT32_MAX ? INT64_MAX : start + 1;
output_shape[norm_axis] = Dimension(0, max_out_dim);
output_shape[norm_axis] = Dimension(0, start + 1);
continue;
} else if (step > 0 && stop > 0 && start < 0) {
int64_t max_out_dim = stop >= INT32_MAX ? INT64_MAX : stop;
output_shape[norm_axis] = Dimension(0, max_out_dim);
output_shape[norm_axis] = Dimension(0, stop);
continue;
}
}
src/core/tests/type_prop/slice.cpp
+76 -6
View File
@@ -386,7 +386,7 @@ TEST(type_prop, slice_v8_basic_const_inputs_MAX_MIN_INT_dynamic_dimensions) {
Dimension(10, 20),
Dimension(30, 40),
Dimension(0, 50),
Dimension(0, INT32_MAX)};
Dimension(-1)};
std::vector<int32_t> start_val{2, 2, INT32_MIN, INT32_MIN, INT32_MIN, INT32_MIN, INT32_MIN, 0, 0};
std::vector<int32_t> stop_val{10, INT32_MAX, 5, 10, 15, 25, INT32_MAX, 50, INT32_MAX};
@@ -536,11 +536,7 @@ TEST(type_prop, slice_v8_basic_const_inputs_data_full_dynamic_dims_neg_step_neg_
TEST(type_prop, slice_v8_basic_const_inputs_data_full_dynamic_dims_neg_step_mix_ind) {
PartialShape data_shape{Dimension(-1), Dimension(-1), Dimension(-1), Dimension(-1), Dimension(-1)};
PartialShape expected_out_shape{Dimension(0, 6),
Dimension(0, 6),
Dimension(-1),
Dimension(0, INT32_MAX - 5),
Dimension(-1)};
PartialShape expected_out_shape{Dimension(0, 6), Dimension(0, 6), Dimension(-1), Dimension(0, -1), Dimension(-1)};
std::vector<int32_t> start_val{5, 5, -10, INT32_MAX, INT32_MAX};
std::vector<int32_t> stop_val{-10, INT32_MIN, 5, 5, INT32_MIN};
@@ -557,6 +553,80 @@ TEST(type_prop, slice_v8_basic_const_inputs_data_full_dynamic_dims_neg_step_mix_
EXPECT_EQ(op->get_output_partial_shape(0), expected_out_shape);
}
TEST(type_prop, slice_v8_basic_const_inputs_dynamic_dims_maxint32) {
PartialShape data_shape{Dimension(0, 2000), Dimension(-1), 4};
PartialShape expected_out_shape{Dimension(0, 2000), Dimension(-1), Dimension(4)};
std::vector<int32_t> start_val{0, 0, 0};
std::vector<int32_t> stop_val{INT32_MAX, INT32_MAX, INT32_MAX};
std::vector<int32_t> step_val{1, 1, 1};
std::vector<int32_t> axes_val(start_val.size());
std::iota(axes_val.begin(), axes_val.end(), 0);
element::Type_t et = element::i32;
std::vector<std::vector<int32_t>> input_vals{start_val, stop_val, step_val, axes_val};
const auto op = make_slice_op_const_inputs(input_vals, data_shape, et);
EXPECT_EQ(op->get_element_type(), et);
EXPECT_EQ(op->get_output_partial_shape(0), expected_out_shape);
}
TEST(type_prop, slice_v8_basic_const_inputs_dynamic_dims_maxint64) {
PartialShape data_shape{Dimension(0, 2000), Dimension(-1), 4};
PartialShape expected_out_shape{Dimension(0, 2000), Dimension(-1), Dimension(4)};
std::vector<int64_t> start_val{0, 0, 0};
std::vector<int64_t> stop_val{INT64_MAX, INT64_MAX, INT64_MAX};
std::vector<int64_t> step_val{1, 1, 1};
std::vector<int64_t> axes_val(start_val.size());
std::iota(axes_val.begin(), axes_val.end(), 0);
element::Type_t et = element::i64;
std::vector<std::vector<int64_t>> input_vals{start_val, stop_val, step_val, axes_val};
const auto op = make_slice_op_const_inputs(input_vals, data_shape, et);
EXPECT_EQ(op->get_element_type(), et);
EXPECT_EQ(op->get_output_partial_shape(0), expected_out_shape);
}
TEST(type_prop, slice_v8_basic_const_inputs_dynamic_dims_maxint32_start1) {
PartialShape data_shape{Dimension(0, 2000), Dimension(-1), 4};
PartialShape expected_out_shape{Dimension(0, 2000), Dimension(-1), Dimension(4)};
std::vector<int32_t> start_val{1};
std::vector<int32_t> stop_val{INT32_MAX};
std::vector<int32_t> step_val{1};
std::vector<int32_t> axes_val{1};
element::Type_t et = element::i32;
std::vector<std::vector<int32_t>> input_vals{start_val, stop_val, step_val, axes_val};
const auto op = make_slice_op_const_inputs(input_vals, data_shape, et);
EXPECT_EQ(op->get_element_type(), et);
EXPECT_EQ(op->get_output_partial_shape(0), expected_out_shape);
}
TEST(type_prop, slice_v8_basic_const_inputs_dynamic_dims_maxint64_start1) {
PartialShape data_shape{Dimension(0, 2000), Dimension(-1), 4};
PartialShape expected_out_shape{Dimension(0, 2000), Dimension(-1), Dimension(4)};
std::vector<int64_t> start_val{1};
std::vector<int64_t> stop_val{INT64_MAX};
std::vector<int64_t> step_val{1};
std::vector<int64_t> axes_val{1};
element::Type_t et = element::i64;
std::vector<std::vector<int64_t>> input_vals{start_val, stop_val, step_val, axes_val};
const auto op = make_slice_op_const_inputs(input_vals, data_shape, et);
EXPECT_EQ(op->get_element_type(), et);
EXPECT_EQ(op->get_output_partial_shape(0), expected_out_shape);
}
TEST(type_prop, slice_v8_basic_const_inputs_MAX_MIN_INT_64_dynamic_dimensions_neg_step) {
PartialShape data_shape{10,
Dimension(10, 20),