haojin2 commented on a change in pull request #15987: Numpy add numpy op rot90
URL: https://github.com/apache/incubator-mxnet/pull/15987#discussion_r318874434
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File path: src/operator/numpy/np_matrix_op-inl.h
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@@ -60,6 +60,246 @@ void NumpyTranspose(const nnvm::NodeAttrs& attrs,
}
}
+struct NumpyRot90Param : public dmlc::Parameter<NumpyRot90Param> {
+ int k;
+ dmlc::optional<mxnet::TShape> axes;
+ DMLC_DECLARE_PARAMETER(NumpyRot90Param) {
+ DMLC_DECLARE_FIELD(k)
+ .set_default(1)
+ .describe("Number of times the array is rotated by 90 degrees.");
+ DMLC_DECLARE_FIELD(axes)
+ .set_default(dmlc::optional<mxnet::TShape>())
+ .describe(" The array is rotated in the plane defined by the axes. Axes
must be different.");
+ }
+};
+
+struct rot90reverse {
+ MSHADOW_XINLINE static index_t ReverseIndex(index_t idx,
+ index_t nreversedim,
+ const index_t * stride_,
+ const index_t * trailing_) {
+ index_t outputIndex = idx;
+ for (index_t i = 0; i < nreversedim; ++i) {
+ const index_t low = outputIndex % trailing_[i];
+ index_t high = outputIndex / trailing_[i];
+ const index_t x = high % stride_[i];
+ high /= stride_[i];
+ outputIndex = (high * stride_[i] + stride_[i] - 1 - x) * trailing_[i] +
low;
+ }
+ return outputIndex;
+ }
+ template<typename DType>
+ MSHADOW_XINLINE static void Map(index_t index, index_t nreversedim, const
DType *src, DType *dst,
+ const index_t * stride_,
+ const index_t * trailing_) {
+ index_t new_idx = ReverseIndex(index, nreversedim, stride_, trailing_);
+ dst[new_idx] = src[index];
+ }
+};
+
+template<typename xpu>
+void NumpyRot90ComputeFlipIml(const OpContext& ctx,
+ const std::vector<TBlob>& inputs,
+ const std::vector<OpReqType>& req,
+ const std::vector<TBlob>& outputs,
+ const index_t axis0, const index_t axis1) {
+ using namespace mshadow;
+ using namespace mxnet_op;
+
+ const mxnet::TShape& ishape = inputs[0].shape_;
+ Stream<xpu> *s = ctx.get_stream<xpu>();
+
+ std::vector<index_t> stride_(2);
+ std::vector<index_t> trailing_(2);
+ index_t reverse_index = 0;
+ std::vector<index_t> temp{axis0, axis1};
+ for (int axis : temp) {
+ stride_[reverse_index] = ishape[axis];
+ trailing_[reverse_index] = 1;
+ for (int i2 = axis + 1; i2 < ishape.ndim(); ++i2) {
+ trailing_[reverse_index] *= ishape[i2];
+ }
+ reverse_index++;
+ }
+
+ index_t workspace_size = 2 * sizeof(index_t);
+ Tensor<xpu, 1, char> workspace =
+ ctx.requested[0].get_space_typed<xpu, 1, char>(Shape1(2 *
workspace_size), s);
+ Tensor<cpu, 1, index_t> stride_cpu_tensor(stride_.data(),
Shape1(stride_.size()));
+ Tensor<xpu, 1, index_t> stride_xpu_tensor(
+ reinterpret_cast<index_t*>(workspace.dptr_), Shape1(stride_.size()));
+ Tensor<cpu, 1, index_t> trailing_cpu_tensor(trailing_.data(),
Shape1(trailing_.size()));
+ Tensor<xpu, 1, index_t> trailing_xpu_tensor(
+ reinterpret_cast<index_t*>(workspace.dptr_ + workspace_size),
Shape1(trailing_.size()));
+
+ mshadow::Copy(stride_xpu_tensor, stride_cpu_tensor, s);
+ mshadow::Copy(trailing_xpu_tensor, trailing_cpu_tensor, s);
+ MSHADOW_TYPE_SWITCH(outputs[0].type_flag_, DType, {
+ Kernel<rot90reverse, xpu>::Launch(s, inputs[0].Size(),
reverse_index,
Review comment:
Pay attention to the indentation.
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