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cmake: AVX512 -> AVX_512F
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@@ -384,7 +384,7 @@ public:
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p.is1x1_ = kernel == Size(0,0) && pad == Size(0, 0);
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p.useAVX = checkHardwareSupport(CPU_AVX);
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p.useAVX2 = checkHardwareSupport(CPU_AVX2);
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p.useAVX512 = checkHardwareSupport(CPU_AVX_512DQ);
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p.useAVX512 = CV_CPU_HAS_SUPPORT_AVX_512F;
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int ncn = std::min(inpCn, (int)BLK_SIZE_CN);
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p.ofstab_.resize(kernel.width*kernel.height*ncn);
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@@ -564,10 +564,10 @@ public:
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// now compute dot product of the weights
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// and im2row-transformed part of the tensor
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int bsz = ofs1 - ofs0;
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#if CV_TRY_AVX512
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#if CV_TRY_AVX_512F
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/* AVX512 convolution requires an alignment of 16, and ROI is only there for larger vector sizes */
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if(useAVX512)
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opt_AVX512::fastConv(wptr, wstep, biasptr, rowbuf0, data_out0 + ofs0,
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opt_AVX_512F::fastConv(wptr, wstep, biasptr, rowbuf0, data_out0 + ofs0,
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outShape, bsz, vsz, vsz_a, relu, cn0 == 0);
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else
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#endif
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@@ -1102,7 +1102,7 @@ public:
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nstripes_ = nstripes;
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useAVX = checkHardwareSupport(CPU_AVX);
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useAVX2 = checkHardwareSupport(CPU_AVX2);
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useAVX512 = checkHardwareSupport(CPU_AVX_512DQ);
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useAVX512 = CV_CPU_HAS_SUPPORT_AVX_512F;
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}
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void operator()(const Range& range_) const
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@@ -1120,9 +1120,9 @@ public:
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size_t bstep = b_->step1();
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size_t cstep = c_->step1();
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#if CV_TRY_AVX512
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#if CV_TRY_AVX_512F
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if( useAVX512 )
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opt_AVX512::fastGEMM( aptr, astep, bptr, bstep, cptr, cstep, mmax, kmax, nmax );
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opt_AVX_512F::fastGEMM( aptr, astep, bptr, bstep, cptr, cstep, mmax, kmax, nmax );
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else
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#endif
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#if CV_TRY_AVX2
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