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[operators] Guard max-pooling-nhwc padding arithmetic overflow #11409

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[operators] Guard max-pooling-nhwc padding arithmetic overflow #11409

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77 changes: 69 additions & 8 deletions src/operators/max-pooling-nhwc.c
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Original file line number Diff line number Diff line change
Expand Up @@ -435,30 +435,91 @@ static enum xnn_status reshape_max_pooling2d_nhwc(
max_pooling_op->convolution_op->input_height = input_height;
max_pooling_op->convolution_op->input_width = input_width;

size_t effective_kernel_height;
size_t effective_kernel_width;
if (max_pooling_op->convolution_op->kernel_height == 0 ||
max_pooling_op->convolution_op->kernel_width == 0 ||
!xnn_safe_mul(
(size_t)(max_pooling_op->convolution_op->kernel_height - 1),
(size_t)max_pooling_op->convolution_op->dilation_height,
&effective_kernel_height) ||
!xnn_safe_add(effective_kernel_height, 1, &effective_kernel_height) ||
!xnn_safe_mul(
(size_t)(max_pooling_op->convolution_op->kernel_width - 1),
(size_t)max_pooling_op->convolution_op->dilation_width,
&effective_kernel_width) ||
!xnn_safe_add(effective_kernel_width, 1, &effective_kernel_width)) {
xnn_log_error(
"failed to reshape %s operator: effective kernel size overflows size_t",
xnn_operator_type_to_string_v2(max_pooling_op));
return xnn_status_out_of_memory;
}

if (max_pooling_op->flags & XNN_FLAG_TENSORFLOW_SAME_PADDING) {
max_pooling_op->convolution_op->output_height = compute_output_dimension_with_tf_same_padding(
input_height, max_pooling_op->convolution_op->stride_height);
max_pooling_op->convolution_op->output_width = compute_output_dimension_with_tf_same_padding(
input_width, max_pooling_op->convolution_op->stride_width);

const size_t effective_kernel_height = (size_t)(max_pooling_op->convolution_op->kernel_height - 1) * max_pooling_op->convolution_op->dilation_height + 1;
const size_t effective_kernel_width = (size_t)(max_pooling_op->convolution_op->kernel_width - 1) * max_pooling_op->convolution_op->dilation_width + 1;
const uint32_t total_padding_height =
doz((max_pooling_op->convolution_op->output_height - 1) * max_pooling_op->convolution_op->stride_height + effective_kernel_height, input_height);
const uint32_t total_padding_width =
doz((max_pooling_op->convolution_op->output_width - 1) * max_pooling_op->convolution_op->stride_width + effective_kernel_width, input_width);
size_t scaled_output_height;
size_t scaled_output_width;
size_t total_input_height;
size_t total_input_width;
if (max_pooling_op->convolution_op->output_height == 0 ||
max_pooling_op->convolution_op->output_width == 0 ||
!xnn_safe_mul(max_pooling_op->convolution_op->output_height - 1,
max_pooling_op->convolution_op->stride_height,
&scaled_output_height) ||
!xnn_safe_add(scaled_output_height, effective_kernel_height,
&total_input_height) ||
!xnn_safe_mul(max_pooling_op->convolution_op->output_width - 1,
max_pooling_op->convolution_op->stride_width,
&scaled_output_width) ||
!xnn_safe_add(scaled_output_width, effective_kernel_width,
&total_input_width)) {
xnn_log_error(
"failed to reshape %s operator: padding calculation overflows size_t",
xnn_operator_type_to_string_v2(max_pooling_op));
return xnn_status_out_of_memory;
}
const size_t total_padding_height = doz(total_input_height, input_height);
const size_t total_padding_width = doz(total_input_width, input_width);
if (total_padding_height > UINT32_MAX ||
total_padding_width > UINT32_MAX) {
xnn_log_error(
"failed to reshape %s operator: padding exceeds uint32_t range",
xnn_operator_type_to_string_v2(max_pooling_op));
return xnn_status_out_of_memory;
}
max_pooling_op->convolution_op->padding_top = total_padding_height / 2;
max_pooling_op->convolution_op->padding_left = total_padding_width / 2;
max_pooling_op->convolution_op->padding_bottom = total_padding_height - max_pooling_op->convolution_op->padding_top;
max_pooling_op->convolution_op->padding_right = total_padding_width - max_pooling_op->convolution_op->padding_left;
} else {
size_t padded_input_height;
size_t padded_input_width;
if (!xnn_safe_add(max_pooling_op->convolution_op->padding_top,
input_height, &padded_input_height) ||
!xnn_safe_add(padded_input_height,
max_pooling_op->convolution_op->padding_bottom,
&padded_input_height) ||
!xnn_safe_add(max_pooling_op->convolution_op->padding_left, input_width,
&padded_input_width) ||
!xnn_safe_add(padded_input_width,
max_pooling_op->convolution_op->padding_right,
&padded_input_width)) {
xnn_log_error(
"failed to reshape %s operator: padded input size overflows size_t",
xnn_operator_type_to_string_v2(max_pooling_op));
return xnn_status_out_of_memory;
}
max_pooling_op->convolution_op->output_height = xnn_compute_convolution_output_dimension(
max_pooling_op->convolution_op->padding_top + input_height + max_pooling_op->convolution_op->padding_bottom,
padded_input_height,
max_pooling_op->convolution_op->kernel_height,
max_pooling_op->convolution_op->dilation_height,
max_pooling_op->convolution_op->stride_height);
max_pooling_op->convolution_op->output_width = xnn_compute_convolution_output_dimension(
max_pooling_op->convolution_op->padding_left + input_width + max_pooling_op->convolution_op->padding_right,
padded_input_width,
max_pooling_op->convolution_op->kernel_width,
max_pooling_op->convolution_op->dilation_width,
max_pooling_op->convolution_op->stride_width);
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27 changes: 27 additions & 0 deletions test/operators/max-pooling-nhwc.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -1919,6 +1919,33 @@ TEST(MAX_POOLING_NHWC_F32, reshape_overflow_input_stride) {
&output_height, &output_width, nullptr));
}

TEST(MAX_POOLING_NHWC_F32, padded_input_height_overflow) {
ASSERT_EQ(xnn_status_success, xnn_initialize(/*allocator=*/nullptr));
xnn_operator_t max_pooling_op = nullptr;
const xnn_status status = xnn_create_max_pooling2d_nhwc_f32(
/*padding_top=*/0, /*padding_right=*/0, /*padding_bottom=*/1,
/*padding_left=*/0, /*pooling_height=*/1, /*pooling_width=*/1,
/*stride_height=*/1, /*stride_width=*/1, /*dilation_height=*/1,
/*dilation_width=*/1, -std::numeric_limits<float>::infinity(),
std::numeric_limits<float>::infinity(), /*flags=*/0, &max_pooling_op);
if (status == xnn_status_unsupported_hardware) {
GTEST_SKIP();
}
ASSERT_EQ(xnn_status_success, status);
std::unique_ptr<xnn_operator, decltype(&xnn_delete_operator)> auto_op(
max_pooling_op, xnn_delete_operator);

size_t output_height = 0;
size_t output_width = 0;
EXPECT_EQ(
xnn_status_out_of_memory,
xnn_reshape_max_pooling2d_nhwc_f32(
max_pooling_op, /*batch_size=*/1, /*input_height=*/SIZE_MAX,
/*input_width=*/1, /*channels=*/1, /*input_pixel_stride=*/1,
/*output_pixel_stride=*/1, &output_height, &output_width,
/*threadpool=*/nullptr));
}

TEST(MAX_POOLING_NHWC_F32, reshape_overflow_output_stride) {
ASSERT_EQ(xnn_status_success, xnn_initialize(nullptr /* allocator */));
xnn_operator_t max_pooling_op = nullptr;
Expand Down
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