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[OpenCL]fix tf_shufflenet model segmentation bug #5777

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merged 2 commits into from
Mar 23, 2021
Merged

[OpenCL]fix tf_shufflenet model segmentation bug #5777

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1e7673a
fix tf_shufflenet model segmentation bug test=develop
daming5432 Mar 23, 2021
ac8fa82
add unsupport cue test=develop
daming5432 Mar 23, 2021
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42 changes: 36 additions & 6 deletions lite/kernels/opencl/layout_image_compute.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -80,8 +80,18 @@ class LayoutComputeBufferChwToImageDefault

// out info
std::vector<size_t> new_dims = {1, 1, 1, 1};
for (int tidx = 0; tidx < x_dims.size(); ++tidx) {
new_dims[4 - x_dims.size() + tidx] = x_dims[tidx];
if (x_dims.size() == 5) {
new_dims[4 - x_dims.size() + 1] = x_dims[0] * x_dims[1];
for (int tidx = 2; tidx < x_dims.size(); ++tidx) {
new_dims[4 - x_dims.size() + tidx] = x_dims[tidx];
}
} else if (x_dims.size() < 5) {
for (int tidx = 0; tidx < x_dims.size(); ++tidx) {
new_dims[4 - x_dims.size() + tidx] = x_dims[tidx];
}
} else {
LOG(FATAL) << "unsupported layout tensor dims size, the dims size is:"
<< x_dims.size();
}
const int out_C = new_dims[1];
const int out_H = new_dims[2];
Expand Down Expand Up @@ -207,8 +217,18 @@ class LayoutComputeImageDefaultToBufferChw
auto x_image_shape = InitImageDimInfoWith(x_dims);

std::vector<size_t> new_dims = {1, 1, 1, 1};
for (int j = 0; j < x_dims.size(); ++j) {
new_dims[4 - x_dims.size() + j] = x_dims[j];
if (x_dims.size() == 5) {
new_dims[4 - x_dims.size() + 1] = x_dims[0] * x_dims[1];
for (int j = 2; j < x_dims.size(); ++j) {
new_dims[4 - x_dims.size() + j] = x_dims[j];
}
} else if (x_dims.size() < 5) {
for (int j = 0; j < x_dims.size(); ++j) {
new_dims[4 - x_dims.size() + j] = x_dims[j];
}
} else {
LOG(FATAL) << "unsupported layout tensor dims size, the dims size is: "
<< x_dims.size();
}

#ifdef LITE_WITH_LOG
Expand Down Expand Up @@ -322,8 +342,18 @@ class LayoutComputeBufferChwToImage2DNw

// out info
std::vector<size_t> new_dims = {1, 1, 1, 1};
for (int tidx = 0; tidx < x_dims.size(); ++tidx) {
new_dims[4 - x_dims.size() + tidx] = x_dims[tidx];
if (x_dims.size() == 5) {
new_dims[4 - x_dims.size() + 1] = x_dims[0] * x_dims[1];
for (int tidx = 2; tidx < x_dims.size(); ++tidx) {
new_dims[4 - x_dims.size() + tidx] = x_dims[tidx];
}
} else if (x_dims.size() < 5) {
for (int tidx = 0; tidx < x_dims.size(); ++tidx) {
new_dims[4 - x_dims.size() + tidx] = x_dims[tidx];
}
} else {
LOG(FATAL) << "unsupported layout tensor dims size, the dims size is:"
<< x_dims.size();
}

const int out_N = new_dims[0];
Expand Down