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- CPU - add padding support - fix bug in permute when channel % 4 != 0 - fix bug in exp with extreme value - OpenCL - add protecting logics - OpenGL - add protecting logics - support NCHW format in Squeeze and Reshape - Converter - add ShuffleChannel support for Caffe - add Clip/Transpose/Unary/Pad supports for ONNX
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,93 @@ | ||
| // | ||
| // CPUPadding.cpp | ||
| // MNN | ||
| // | ||
| // Created by MNN on 2019/6/24. | ||
| // Copyright © 2018 Alibaba. All rights reserved. | ||
| // | ||
|
|
||
| #include "CPUPadding.hpp" | ||
| #include "Macro.h" | ||
| #include "TensorUtils.hpp" | ||
| namespace MNN { | ||
| ErrorCode CPUPadding::onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) { | ||
| auto input = inputs[0]; | ||
| auto output = outputs[0]; | ||
| auto padding = inputs[1]->host<int32_t>(); | ||
| ::memset(output->host<char>(), 0, output->size()); | ||
| auto bytes = input->getType().bytes(); | ||
| auto unit = input->length(3) * bytes; | ||
| for (int b = 0; b < input->length(0); ++b) { | ||
| auto outputB = output->host<char>() + output->stride(0) * (b + padding[2 * 0]) * bytes; | ||
| auto inputB = input->host<char>() + input->stride(0) * b * bytes; | ||
| for (int h = 0; h < input->length(1); ++h) { | ||
| auto outputH = outputB + output->stride(1) * (h + padding[2 * 1]) * bytes; | ||
| auto inputH = inputB + input->stride(1) * h * bytes; | ||
| for (int w = 0; w < input->length(2); ++w) { | ||
| auto outputW = outputH + output->stride(2) * (w + padding[2 * 2]) * bytes; | ||
| auto inputW = inputH + input->stride(2) * w * bytes; | ||
| ::memcpy(outputW + padding[3 * 2] * bytes, inputW, unit); | ||
| } | ||
| } | ||
| } | ||
| return NO_ERROR; | ||
| } | ||
|
|
||
| ErrorCode CPUPaddingPacked::onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) { | ||
| auto input = inputs[0]; | ||
| auto output = outputs[0]; | ||
| auto iw = input->width(); | ||
| auto ih = input->height(); | ||
| auto ic = input->channel(); | ||
| auto ib = input->batch(); | ||
|
|
||
| auto ow = output->width(); | ||
| auto oh = output->height(); | ||
| auto icC4 = UP_DIV(ic, 4); | ||
| auto padding = inputs[1]->host<int32_t>(); | ||
| ::memset(output->host<float>(), 0, output->size()); | ||
| for (int n = 0; n < ib; ++n) { | ||
| auto inputN = input->host<float>() + input->stride(0) * n; | ||
| auto outputN = output->host<float>() + output->stride(0) * (padding[2 * 0] + n); | ||
| for (int c = 0; c < icC4; ++c) { | ||
| auto inputC = inputN + c * iw * ih * 4; | ||
| auto outputC = outputN + c * ow * oh * 4; | ||
|
|
||
| for (int h = 0; h < ih; ++h) { | ||
| auto inputH = inputC + h * iw * 4; | ||
| auto outputH = outputC + (h + padding[2 * 2]) * ow * 4; | ||
|
|
||
| ::memcpy(outputH + padding[2 * 3] * 4, inputH, iw * 4 * sizeof(float)); | ||
| } | ||
| } | ||
| } | ||
|
|
||
| return NO_ERROR; | ||
| } | ||
| class CPUPaddingCreator : public CPUBackend::Creator { | ||
| public: | ||
| virtual Execution *onCreate(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs, | ||
| const MNN::Op *op, Backend *backend) const { | ||
| if (inputs[0]->dimensions() != 4) { | ||
| MNN_ERROR("Currently padding only support NHWC or NC4HW4\n"); | ||
| return nullptr; | ||
| } | ||
| auto padding = inputs[1]; | ||
| auto paddingPtr = padding->host<int32_t>(); | ||
| if (TensorUtils::getDescribe(inputs[0])->dimensionFormat == MNN_DATA_FORMAT_NHWC) { | ||
| return new CPUPadding(backend); | ||
| } | ||
| if (paddingPtr[2] != 0 || paddingPtr[3] != 0) { | ||
| MNN_ERROR("Currently padding NC4HW4 don't support channel padding\n"); | ||
| return nullptr; | ||
| } | ||
| if (inputs[0]->buffer().type.code != halide_type_float) { | ||
| MNN_ERROR("Currently padding NC4HW4 only support float padding\n"); | ||
| return nullptr; | ||
| } | ||
| return new CPUPaddingPacked(backend); | ||
| } | ||
| }; | ||
|
|
||
| REGISTER_CPU_OP_CREATOR(CPUPaddingCreator, OpType_Padding); | ||
| }; // namespace MNN |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,31 @@ | ||
| // | ||
| // CPUPadding.hpp | ||
| // MNN | ||
| // | ||
| // Created by MNN on 2019/6/24. | ||
| // Copyright © 2018 Alibaba. All rights reserved. | ||
| // | ||
|
|
||
| #ifndef CPUPadding_hpp | ||
| #define CPUPadding_hpp | ||
|
|
||
| #include <stdio.h> | ||
| #include "CPUBackend.hpp" | ||
| namespace MNN { | ||
| class CPUPaddingPacked : public Execution { | ||
| public: | ||
| CPUPaddingPacked(Backend *bn) : Execution(bn) { | ||
| // Do nothing | ||
| } | ||
| virtual ErrorCode onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) override; | ||
| }; | ||
| class CPUPadding : public Execution { | ||
| public: | ||
| CPUPadding(Backend *bn) : Execution(bn) { | ||
| // Do nothing | ||
| } | ||
| virtual ErrorCode onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) override; | ||
| }; | ||
| }; // namespace MNN | ||
|
|
||
| #endif /* CPUPadding_hpp */ |
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