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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/9992 Optimize reduce ops for 2d and 3d Reviewed By: houseroad Differential Revision: D9042505 fbshipit-source-id: 62af2125aa6439106293e59bdf6a2b920792fd2d
310 lines
7 KiB
C++
310 lines
7 KiB
C++
#include "caffe2/utils/math_utils.h"
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#include <algorithm>
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#include <functional>
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#include <numeric>
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#include <vector>
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#include "caffe2/core/logging.h"
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namespace caffe2 {
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namespace math {
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namespace utils {
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void IncreaseIndexInDims(const int n, const int* dims, int* index) {
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for (int i = n - 1; i >= 0; --i) {
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++index[i];
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if (index[i] >= dims[i]) {
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index[i] -= dims[i];
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} else {
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break;
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}
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}
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}
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int GetIndexFromDims(const int n, const int* dims, const int* index) {
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int sum = 0;
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for (int i = 0; i < n; ++i) {
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if (dims[i] > 1) {
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sum = sum * dims[i] + index[i];
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}
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}
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return sum;
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}
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bool IsIdentityPermutation(const int n, const int* perm) {
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for (int i = 0; i < n; ++i) {
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if (perm[i] != i) {
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return false;
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}
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}
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return true;
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}
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bool IsRowwiseReduce(
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const int ndim,
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const int* A_dims,
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const int* B_dims,
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int* rows,
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int* cols) {
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*cols = 1;
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int pivot = ndim - 1;
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for (; pivot >= 0 && B_dims[pivot] == 1; --pivot) {
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*cols *= A_dims[pivot];
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}
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*rows = 1;
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for (int i = pivot; i >= 0; --i) {
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if (A_dims[i] != B_dims[i]) {
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return false;
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}
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*rows *= A_dims[i];
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}
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return true;
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}
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bool IsColwiseReduce(
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const int ndim,
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const int* A_dims,
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const int* B_dims,
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int* rows,
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int* cols) {
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*rows = 1;
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int pivot = 0;
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for (; pivot < ndim && B_dims[pivot] == 1; ++pivot) {
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*rows *= A_dims[pivot];
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}
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*cols = 1;
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for (int i = pivot; i < ndim; ++i) {
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if (A_dims[i] != B_dims[i]) {
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return false;
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}
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*cols *= A_dims[i];
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}
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return true;
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}
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bool IsBothEndsReduce(
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const int ndim,
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const int* A_dims,
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const int* B_dims,
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int* pre,
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int* mid,
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int* nxt) {
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*nxt = 1;
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int r = ndim - 1;
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for (; r >= 0 && B_dims[r] == 1; --r) {
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*nxt *= A_dims[r];
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}
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*pre = 1;
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int l = 0;
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for (; l <= r && B_dims[l] == 1; ++l) {
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*pre *= A_dims[l];
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}
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*mid = 1;
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for (int i = l; i <= r; ++i) {
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if (A_dims[i] != B_dims[i]) {
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return false;
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}
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*mid *= A_dims[i];
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}
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return true;
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}
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void ComputeBroadcastBinaryOpDims(
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const int A_ndim,
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const int* A_dims,
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const int B_ndim,
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const int* B_dims,
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int* A_broadcast_dims,
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int* B_broadcast_dims,
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int* C_broadcast_dims) {
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const int ndim = std::max(A_ndim, B_ndim);
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std::fill(A_broadcast_dims, A_broadcast_dims + ndim - A_ndim, 1);
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std::fill(B_broadcast_dims, B_broadcast_dims + ndim - B_ndim, 1);
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std::copy(A_dims, A_dims + A_ndim, A_broadcast_dims + ndim - A_ndim);
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std::copy(B_dims, B_dims + B_ndim, B_broadcast_dims + ndim - B_ndim);
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for (int i = 0; i < ndim; ++i) {
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CAFFE_ENFORCE(
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A_broadcast_dims[i] == B_broadcast_dims[i] ||
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A_broadcast_dims[i] <= 1 || B_broadcast_dims[i] <= 1);
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if (A_broadcast_dims[i] == 0 || B_broadcast_dims[i] == 0) {
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C_broadcast_dims[i] = 0;
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} else {
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C_broadcast_dims[i] = std::max(A_broadcast_dims[i], B_broadcast_dims[i]);
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}
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}
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}
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bool IsRowwiseBroadcastBinaryOp(
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const int ndim,
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const int* A_dims,
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const int* B_dims,
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int* rows,
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int* cols,
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bool* broadcast_1st) {
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if (ndim == 0) {
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return false;
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}
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int A_pivot = 0;
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for (; A_pivot < ndim && A_dims[A_pivot] == 1; ++A_pivot)
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;
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int B_pivot = 0;
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for (; B_pivot < ndim && B_dims[B_pivot] == 1; ++B_pivot)
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;
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if (A_pivot == B_pivot) {
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return false;
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}
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const int pivot = std::max(A_pivot, B_pivot);
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if (A_pivot > B_pivot) {
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*rows = std::accumulate(
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B_dims + B_pivot, B_dims + pivot, 1, std::multiplies<int>());
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*broadcast_1st = true;
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} else {
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*rows = std::accumulate(
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A_dims + A_pivot, A_dims + pivot, 1, std::multiplies<int>());
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*broadcast_1st = false;
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}
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*cols = 1;
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for (int i = pivot; i < ndim; ++i) {
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if (A_dims[i] != B_dims[i]) {
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return false;
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}
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*cols *= A_dims[i];
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}
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return true;
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}
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bool IsColwiseBroadcastBinaryOp(
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const int ndim,
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const int* A_dims,
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const int* B_dims,
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int* rows,
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int* cols,
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bool* broadcast_1st) {
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if (ndim == 0) {
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return false;
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}
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int A_pivot = ndim - 1;
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for (; A_pivot >= 0 && A_dims[A_pivot] == 1; --A_pivot)
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;
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int B_pivot = ndim - 1;
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for (; B_pivot >= 0 && B_dims[B_pivot] == 1; --B_pivot)
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;
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if (A_pivot == B_pivot) {
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return false;
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}
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++A_pivot;
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++B_pivot;
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const int pivot = std::min(A_pivot, B_pivot);
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if (A_pivot < B_pivot) {
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*cols = std::accumulate(
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B_dims + pivot, B_dims + B_pivot, 1, std::multiplies<int>());
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*broadcast_1st = true;
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} else {
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*cols = std::accumulate(
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A_dims + pivot, A_dims + A_pivot, 1, std::multiplies<int>());
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*broadcast_1st = false;
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}
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*rows = 1;
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for (int i = 0; i < pivot; ++i) {
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if (A_dims[i] != B_dims[i]) {
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return false;
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}
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*rows *= A_dims[i];
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}
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return true;
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}
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bool IsBothEndsBroadcastBinaryOp(
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const int ndim,
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const int* A_dims,
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const int* B_dims,
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int* pre,
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int* mid,
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int* nxt,
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bool* broadcast_1st) {
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if (ndim == 0) {
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return false;
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}
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int A_pre = 0;
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for (; A_pre < ndim && A_dims[A_pre] == 1; ++A_pre)
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;
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int B_pre = 0;
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for (; B_pre < ndim && B_dims[B_pre] == 1; ++B_pre)
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;
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int A_nxt = ndim - 1;
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for (; A_nxt >= 0 && A_dims[A_nxt] == 1; --A_nxt)
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;
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int B_nxt = ndim - 1;
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for (; B_nxt >= 0 && B_dims[B_nxt] == 1; --B_nxt)
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;
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++A_nxt;
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++B_nxt;
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if (A_pre == B_pre || A_nxt == B_nxt) {
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return false;
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}
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if (A_pre > B_pre && A_nxt < B_nxt) {
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*pre = std::accumulate(
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B_dims + B_pre, B_dims + A_pre, 1, std::multiplies<int>());
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*nxt = std::accumulate(
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B_dims + A_nxt, B_dims + B_nxt, 1, std::multiplies<int>());
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*broadcast_1st = true;
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} else if (A_pre < B_pre && A_nxt > B_nxt) {
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*pre = std::accumulate(
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A_dims + A_pre, A_dims + B_pre, 1, std::multiplies<int>());
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*nxt = std::accumulate(
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A_dims + B_nxt, A_dims + A_nxt, 1, std::multiplies<int>());
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*broadcast_1st = false;
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} else {
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return false;
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}
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const int l = std::max(A_pre, B_pre);
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const int r = std::min(A_nxt, B_nxt);
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*mid = 1;
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for (int i = l; i < r; ++i) {
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if (A_dims[i] != B_dims[i]) {
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return false;
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}
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*mid *= A_dims[i];
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}
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return true;
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}
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void ComputeTransposeAxesForReduceOp(
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const int num_dims,
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const int num_reduce_axes,
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const int* reduce_axes,
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int* transpose_axes) {
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const int d = num_dims - num_reduce_axes;
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std::copy_n(reduce_axes, num_reduce_axes, transpose_axes + d);
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std::sort(transpose_axes + d, transpose_axes + num_dims);
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int p = 0;
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int q = d;
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for (int i = 0; i < num_dims; ++i) {
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if (q < num_dims && i == transpose_axes[q]) {
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++q;
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} else {
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transpose_axes[p++] = i;
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}
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}
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}
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void ComputeTransposedStrides(
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const int ndim,
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const int* dims,
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const int* axes,
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int* strides) {
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std::vector<int> buff(ndim);
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int cur_stride = 1;
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for (int i = ndim - 1; i >= 0; --i) {
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buff[i] = cur_stride;
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cur_stride *= dims[i];
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}
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for (int i = 0; i < ndim; ++i) {
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strides[i] = buff[axes[i]];
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}
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}
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} // namespace utils
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} // namespace math
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} // namespace caffe2
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