mirror of
https://github.com/Tencent/ncnn.git
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nihui
f6f734f44d
* vulkan: add int8 kernels for core layers Implement Vulkan int8 paths for convolution, convolutiondepthwise, innerproduct, and gemm with scalar fallback and integer dot product shader branches. Add goal.md and enable existing int8 unit tests for Vulkan coverage. * enable int8 gpu benchmark
600 lines
22 KiB
C++
600 lines
22 KiB
C++
// Copyright 2024 Tencent
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// SPDX-License-Identifier: BSD-3-Clause
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#include "testutil.h"
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#if NCNN_INT8
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static void RandomizeA(ncnn::Mat& m, int transA, float absmax)
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{
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if (transA == 0)
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{
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const int h = m.dims == 3 ? m.c : m.h;
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for (int i = 0; i < h; i++)
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{
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float* p = m.dims == 3 ? m.channel(i) : m.row(i);
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float randabsmax = RandomFloat(absmax * 0.5f, absmax);
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randabsmax = ncnn::float16_to_float32(ncnn::float32_to_float16(randabsmax));
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randabsmax = ncnn::bfloat16_to_float32(ncnn::float32_to_bfloat16(randabsmax));
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for (int j = 0; j < m.w; j++)
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{
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p[j] = RandomFloat(-randabsmax, randabsmax);
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}
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// set random a and b
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p[RandomInt(0, m.w - 1)] = -randabsmax;
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p[RandomInt(0, m.w - 1)] = randabsmax;
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// drop 0.45 ~ 0.55
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for (int j = 0; j < m.w; j++)
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{
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float v = p[j] * (127.f / randabsmax);
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float vv = fabs(v - (int)v);
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float hp = ncnn::float16_to_float32(ncnn::float32_to_float16(p[j]));
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float hv = hp * (127.f / randabsmax);
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float hvv = fabs(hv - (int)hv);
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float bp = ncnn::bfloat16_to_float32(ncnn::float32_to_bfloat16(p[j]));
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float bv = bp * (127.f / randabsmax);
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float bvv = fabs(bv - (int)bv);
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while ((vv > 0.45f && vv < 0.55f) || (hvv > 0.45f && hvv < 0.55f) || (bvv > 0.45f && bvv < 0.55f))
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{
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p[j] = RandomFloat(-randabsmax, randabsmax);
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v = p[j] * (127.f / randabsmax);
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vv = fabs(v - (int)v);
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hp = ncnn::float16_to_float32(ncnn::float32_to_float16(p[j]));
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hv = hp * (127.f / randabsmax);
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hvv = fabs(hv - (int)hv);
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bp = ncnn::bfloat16_to_float32(ncnn::float32_to_bfloat16(p[j]));
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bv = bp * (127.f / randabsmax);
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bvv = fabs(bv - (int)bv);
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}
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}
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}
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}
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else // if (transA == 1)
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{
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std::vector<float> randabsmaxes(m.w);
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for (int j = 0; j < m.w; j++)
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{
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float randabsmax = RandomFloat(absmax * 0.5f, absmax);
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randabsmax = ncnn::float16_to_float32(ncnn::float32_to_float16(randabsmax));
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randabsmax = ncnn::bfloat16_to_float32(ncnn::float32_to_bfloat16(randabsmax));
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randabsmaxes[j] = randabsmax;
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}
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const int h = m.dims == 3 ? m.c : m.h;
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for (int i = 0; i < h; i++)
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{
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float* p = m.dims == 3 ? m.channel(i) : m.row(i);
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for (int j = 0; j < m.w; j++)
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{
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const float randabsmax = randabsmaxes[j];
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p[j] = RandomFloat(-randabsmax, randabsmax);
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}
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// drop 0.45 ~ 0.55
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for (int j = 0; j < m.w; j++)
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{
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const float randabsmax = randabsmaxes[j];
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float v = p[j] * (127.f / randabsmax);
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float vv = fabs(v - (int)v);
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float hp = ncnn::float16_to_float32(ncnn::float32_to_float16(p[j]));
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float hv = hp * (127.f / randabsmax);
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float hvv = fabs(hv - (int)hv);
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float bp = ncnn::bfloat16_to_float32(ncnn::float32_to_bfloat16(p[j]));
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float bv = bp * (127.f / randabsmax);
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float bvv = fabs(bv - (int)bv);
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while ((vv > 0.45f && vv < 0.55f) || (hvv > 0.45f && hvv < 0.55f) || (bvv > 0.45f && bvv < 0.55f))
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{
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p[j] = RandomFloat(-randabsmax, randabsmax);
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v = p[j] * (127.f / randabsmax);
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vv = fabs(v - (int)v);
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hp = ncnn::float16_to_float32(ncnn::float32_to_float16(p[j]));
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hv = hp * (127.f / randabsmax);
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hvv = fabs(hv - (int)hv);
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bp = ncnn::bfloat16_to_float32(ncnn::float32_to_bfloat16(p[j]));
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bv = bp * (127.f / randabsmax);
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bvv = fabs(bv - (int)bv);
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}
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}
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}
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for (int j = 0; j < m.w; j++)
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{
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const int randi0 = RandomInt(0, h - 1);
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const int randi1 = RandomInt(0, h - 1);
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float* p0 = m.dims == 3 ? m.channel(randi0) : m.row(randi0);
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float* p1 = m.dims == 3 ? m.channel(randi1) : m.row(randi1);
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const float randabsmax = randabsmaxes[j];
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// set random a and b
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p0[j] = -randabsmax;
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p1[j] = randabsmax;
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}
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}
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}
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static void RandomizeB(ncnn::Mat& m, float absmax)
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{
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absmax = ncnn::float16_to_float32(ncnn::float32_to_float16(absmax));
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absmax = ncnn::bfloat16_to_float32(ncnn::float32_to_bfloat16(absmax));
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const int h = m.dims == 3 ? m.c : m.h;
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float* p = m;
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for (int i = 0; i < h; i++)
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{
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float* p = m.dims == 3 ? m.channel(i) : m.row(i);
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for (int j = 0; j < m.w; j++)
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{
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p[j] = RandomFloat(-absmax, absmax);
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// drop 0.45 ~ 0.55
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float v = p[j] * (127.f / absmax);
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float vv = fabs(v - (int)v);
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float hp = ncnn::float16_to_float32(ncnn::float32_to_float16(p[j]));
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float hv = hp * (127.f / absmax);
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float hvv = fabs(hv - (int)hv);
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float bp = ncnn::bfloat16_to_float32(ncnn::float32_to_bfloat16(p[j]));
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float bv = bp * (127.f / absmax);
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float bvv = fabs(bv - (int)bv);
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while ((vv > 0.45f && vv < 0.55f) || (hvv > 0.45f && hvv < 0.55f) || (bvv > 0.45f && bvv < 0.55f))
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{
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p[j] = RandomFloat(-absmax, absmax);
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v = p[j] * (127.f / absmax);
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vv = fabs(v - (int)v);
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hp = ncnn::float16_to_float32(ncnn::float32_to_float16(p[j]));
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hv = hp * (127.f / absmax);
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hvv = fabs(hv - (int)hv);
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bp = ncnn::bfloat16_to_float32(ncnn::float32_to_bfloat16(p[j]));
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bv = bp * (127.f / absmax);
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bvv = fabs(bv - (int)bv);
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}
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}
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}
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// set random a and b
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if (m.dims == 3)
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{
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m.channel(RandomInt(0, h - 1))[RandomInt(0, m.w - 1)] = -absmax;
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m.channel(RandomInt(0, h - 1))[RandomInt(0, m.w - 1)] = absmax;
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}
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else
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{
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m.row(RandomInt(0, h - 1))[RandomInt(0, m.w - 1)] = -absmax;
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m.row(RandomInt(0, h - 1))[RandomInt(0, m.w - 1)] = absmax;
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}
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}
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static int test_gemm_int8(int M, int N, int K, float alpha, int transA, int transB, int output_elemtype, int output_transpose, int constantA, int constantB, int output_N1M)
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{
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ncnn::ParamDict pd;
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pd.set(0, alpha);
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pd.set(1, 1.f); // beta
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pd.set(2, transA);
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pd.set(3, transB);
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pd.set(4, constantA);
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pd.set(5, constantB);
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pd.set(6, 1);
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pd.set(7, M);
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pd.set(8, N);
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pd.set(9, K);
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pd.set(10, -1);
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pd.set(11, output_N1M);
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pd.set(13, output_elemtype);
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pd.set(14, output_transpose);
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pd.set(18, 2); // int8_scale_term
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std::vector<ncnn::Mat> weights;
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if (constantA) weights.push_back(transA ? RandomS8Mat(M, K) : RandomS8Mat(K, M));
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if (constantB) weights.push_back(transB ? RandomS8Mat(K, N) : RandomS8Mat(N, K));
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if (constantA) weights.push_back(RandomMat(M, 10.f, 20.f));
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if (constantB) weights.push_back(RandomMat(1, 10.f, 20.f));
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std::vector<ncnn::Mat> a;
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if (!constantA)
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{
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a.push_back(transA ? (output_N1M ? ncnn::Mat(M, 1, K) : ncnn::Mat(M, K)) : (output_N1M ? ncnn::Mat(K, 1, M) : ncnn::Mat(K, M)));
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RandomizeA(a[a.size() - 1], transA, 10.f);
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}
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if (!constantB)
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{
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a.push_back(transB ? (output_N1M ? ncnn::Mat(K, 1, N) : ncnn::Mat(K, N)) : (output_N1M ? ncnn::Mat(N, 1, K) : ncnn::Mat(N, K)));
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RandomizeB(a[a.size() - 1], 10.f);
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}
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ncnn::Option opt;
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opt.num_threads = 1;
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opt.use_packing_layout = true;
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opt.use_fp16_packed = false;
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opt.use_fp16_storage = false;
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opt.use_fp16_arithmetic = false;
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opt.use_bf16_packed = false;
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opt.use_bf16_storage = false;
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int ret = test_layer_opt("Gemm", pd, weights, opt, a);
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if (ret != 0)
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{
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fprintf(stderr, "test_gemm_int8 failed M=%d N=%d K=%d alpha=%f transA=%d transB=%d output_elemtype=%d output_transpose=%d constantA=%d constantB=%d output_N1M=%d\n", M, N, K, alpha, transA, transB, output_elemtype, output_transpose, constantA, constantB, output_N1M);
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}
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return ret;
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}
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static int test_gemm_int8_bias(int M, int N, int K, const ncnn::Mat& C, float alpha, float beta, int transA, int transB, int output_elemtype, int output_transpose, int constantA, int constantB, int constantC, bool use_bf16 = false, int output_N1M = 0)
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{
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int broadcast_type_C = 0;
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if (C.dims == 1 && C.w == 1)
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{
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// scalar
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broadcast_type_C = 0;
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}
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if (C.dims == 1 && C.w == M)
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{
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// M
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// auto broadcast from h to w is the ncnn-style convention
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broadcast_type_C = 1;
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}
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if (C.dims == 1 && C.w == N)
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{
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// N
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broadcast_type_C = 4;
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}
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if (C.dims == 2 && C.w == 1 && C.h == M)
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{
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// Mx1
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broadcast_type_C = 2;
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}
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if (C.dims == 2 && C.w == N && C.h == M)
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{
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// MxN
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broadcast_type_C = 3;
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}
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if (C.dims == 2 && C.w == N && C.h == 1)
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{
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// 1xN
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broadcast_type_C = 4;
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}
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ncnn::ParamDict pd;
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pd.set(0, alpha);
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pd.set(1, beta);
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pd.set(2, transA);
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pd.set(3, transB);
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pd.set(4, constantA);
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pd.set(5, constantB);
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pd.set(6, constantC);
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pd.set(7, M);
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pd.set(8, N);
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pd.set(9, K);
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pd.set(10, broadcast_type_C);
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pd.set(11, output_N1M);
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// pd.set(12, 1); // output_elempack
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pd.set(13, output_elemtype);
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pd.set(14, output_transpose);
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pd.set(18, 2); // int8_scale_term
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std::vector<ncnn::Mat> weights;
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if (constantA) weights.push_back(transA ? RandomS8Mat(M, K) : RandomS8Mat(K, M));
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if (constantB) weights.push_back(transB ? RandomS8Mat(K, N) : RandomS8Mat(N, K));
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if (constantC) weights.push_back(C);
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if (constantA) weights.push_back(RandomMat(M, 10.f, 20.f));
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if (constantB) weights.push_back(RandomMat(1, 10.f, 20.f));
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std::vector<ncnn::Mat> a;
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if (!constantA)
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{
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a.push_back(transA ? (output_N1M ? ncnn::Mat(M, 1, K) : ncnn::Mat(M, K)) : (output_N1M ? ncnn::Mat(K, 1, M) : ncnn::Mat(K, M)));
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RandomizeA(a[a.size() - 1], transA, 10.f);
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}
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if (!constantB)
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{
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a.push_back(transB ? (output_N1M ? ncnn::Mat(K, 1, N) : ncnn::Mat(K, N)) : (output_N1M ? ncnn::Mat(N, 1, K) : ncnn::Mat(N, K)));
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RandomizeB(a[a.size() - 1], 10.f);
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}
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if (!constantC) a.push_back(C);
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ncnn::Option opt;
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opt.num_threads = 1;
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opt.use_packing_layout = true;
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opt.use_fp16_packed = false;
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opt.use_fp16_storage = false;
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opt.use_fp16_arithmetic = false;
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opt.use_bf16_packed = use_bf16;
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opt.use_bf16_storage = use_bf16;
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int ret = test_layer_opt("Gemm", pd, weights, opt, a);
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if (ret != 0)
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{
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fprintf(stderr, "test_gemm_int8_bias failed M=%d N=%d K=%d C.dims=%d C=(%d %d %d) alpha=%f beta=%f transA=%d transB=%d output_elemtype=%d output_transpose=%d constantA=%d constantB=%d constantC=%d use_bf16=%d output_N1M=%d\n", M, N, K, C.dims, C.w, C.h, C.c, alpha, beta, transA, transB, output_elemtype, output_transpose, constantA, constantB, constantC, use_bf16, output_N1M);
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}
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return ret;
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}
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static int test_gemm_int8_fp16s(int M, int N, int K, float alpha, int transA, int transB, int output_elemtype, int output_transpose, int constantA, int constantB, int output_N1M)
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{
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ncnn::ParamDict pd;
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pd.set(0, alpha);
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pd.set(1, 1.f); // beta
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pd.set(2, transA);
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pd.set(3, transB);
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pd.set(4, constantA);
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pd.set(5, constantB);
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pd.set(6, 1);
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pd.set(7, M);
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pd.set(8, N);
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pd.set(9, K);
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pd.set(10, -1);
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pd.set(11, output_N1M);
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pd.set(13, output_elemtype);
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pd.set(14, output_transpose);
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pd.set(18, 2); // int8_scale_term
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std::vector<ncnn::Mat> weights;
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if (constantA) weights.push_back(transA ? RandomS8Mat(M, K) : RandomS8Mat(K, M));
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if (constantB) weights.push_back(transB ? RandomS8Mat(K, N) : RandomS8Mat(N, K));
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if (constantA) weights.push_back(RandomMat(M, 10.f, 20.f));
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if (constantB) weights.push_back(RandomMat(1, 10.f, 20.f));
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std::vector<ncnn::Mat> a;
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if (!constantA)
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{
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a.push_back(transA ? (output_N1M ? ncnn::Mat(M, 1, K) : ncnn::Mat(M, K)) : (output_N1M ? ncnn::Mat(K, 1, M) : ncnn::Mat(K, M)));
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RandomizeA(a[a.size() - 1], transA, 10.f);
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}
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if (!constantB)
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{
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a.push_back(transB ? (output_N1M ? ncnn::Mat(K, 1, N) : ncnn::Mat(K, N)) : (output_N1M ? ncnn::Mat(N, 1, K) : ncnn::Mat(N, K)));
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RandomizeB(a[a.size() - 1], 10.f);
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}
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ncnn::Option opt;
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opt.num_threads = 1;
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opt.use_packing_layout = true;
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opt.use_fp16_packed = false;
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opt.use_fp16_storage = true;
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opt.use_fp16_arithmetic = false;
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opt.use_bf16_packed = false;
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opt.use_bf16_storage = false;
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float epsilon = 0.001;
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int ret = test_layer_opt("Gemm", pd, weights, opt, a, 1, epsilon);
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if (ret != 0)
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{
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fprintf(stderr, "test_gemm_int8_fp16s failed M=%d N=%d K=%d alpha=%f transA=%d transB=%d output_elemtype=%d output_transpose=%d constantA=%d constantB=%d output_N1M=%d\n", M, N, K, alpha, transA, transB, output_elemtype, output_transpose, constantA, constantB, output_N1M);
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return ret;
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}
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return 0;
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}
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static int test_gemm_int8_bf16s(int M, int N, int K, float alpha, int transA, int transB, int output_elemtype, int output_transpose, int constantA, int constantB, int output_N1M)
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{
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ncnn::ParamDict pd;
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pd.set(0, alpha);
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pd.set(1, 1.f); // beta
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pd.set(2, transA);
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pd.set(3, transB);
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pd.set(4, constantA);
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pd.set(5, constantB);
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pd.set(6, 1);
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pd.set(7, M);
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pd.set(8, N);
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pd.set(9, K);
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pd.set(10, -1);
|
|
pd.set(11, output_N1M);
|
|
pd.set(13, output_elemtype);
|
|
pd.set(14, output_transpose);
|
|
pd.set(18, 2); // int8_scale_term
|
|
|
|
std::vector<ncnn::Mat> weights;
|
|
if (constantA) weights.push_back(transA ? RandomS8Mat(M, K) : RandomS8Mat(K, M));
|
|
if (constantB) weights.push_back(transB ? RandomS8Mat(K, N) : RandomS8Mat(N, K));
|
|
if (constantA) weights.push_back(RandomMat(M, 10.f, 20.f));
|
|
if (constantB) weights.push_back(RandomMat(1, 10.f, 20.f));
|
|
|
|
std::vector<ncnn::Mat> a;
|
|
if (!constantA)
|
|
{
|
|
a.push_back(transA ? (output_N1M ? ncnn::Mat(M, 1, K) : ncnn::Mat(M, K)) : (output_N1M ? ncnn::Mat(K, 1, M) : ncnn::Mat(K, M)));
|
|
RandomizeA(a[a.size() - 1], transA, 10.f);
|
|
}
|
|
if (!constantB)
|
|
{
|
|
a.push_back(transB ? (output_N1M ? ncnn::Mat(K, 1, N) : ncnn::Mat(K, N)) : (output_N1M ? ncnn::Mat(N, 1, K) : ncnn::Mat(N, K)));
|
|
RandomizeB(a[a.size() - 1], 10.f);
|
|
}
|
|
|
|
ncnn::Option opt;
|
|
opt.num_threads = 1;
|
|
opt.use_packing_layout = true;
|
|
opt.use_fp16_packed = false;
|
|
opt.use_fp16_storage = false;
|
|
opt.use_fp16_arithmetic = false;
|
|
opt.use_bf16_packed = true;
|
|
opt.use_bf16_storage = true;
|
|
|
|
float epsilon = 0.001;
|
|
|
|
int ret = test_layer_opt("Gemm", pd, weights, opt, a, 1, epsilon);
|
|
if (ret != 0)
|
|
{
|
|
fprintf(stderr, "test_gemm_int8_bf16s failed M=%d N=%d K=%d alpha=%f transA=%d transB=%d output_elemtype=%d output_transpose=%d constantA=%d constantB=%d output_N1M=%d\n", M, N, K, alpha, transA, transB, output_elemtype, output_transpose, constantA, constantB, output_N1M);
|
|
return ret;
|
|
}
|
|
|
|
return 0;
|
|
}
|
|
|
|
static int test_gemm_0(int M, int N, int K)
|
|
{
|
|
return 0
|
|
|| test_gemm_int8(M, N, K, 2.1f, 0, 1, 0, 0, 0, 0, 0)
|
|
|| test_gemm_int8(M, N, K, 3.1f, 1, 1, 0, 0, 0, 0, 0)
|
|
|| test_gemm_int8(M, N, K, 4.1f, 0, 0, 0, 0, 0, 0, 1)
|
|
|| test_gemm_int8(M, N, K, 5.1f, 1, 0, 0, 0, 0, 0, 1)
|
|
|
|
|| test_gemm_int8(M, N, K, 0.2f, 0, 1, 0, 0, 1, 0, 1)
|
|
|| test_gemm_int8(M, N, K, 0.3f, 1, 1, 0, 0, 1, 0, 1)
|
|
|| test_gemm_int8(M, N, K, 0.4f, 0, 0, 0, 0, 0, 1, 0)
|
|
|| test_gemm_int8(M, N, K, 0.5f, 0, 1, 0, 0, 0, 1, 0)
|
|
|
|
|| test_gemm_int8(M, N, K, 1.2f, 0, 1, 0, 0, 1, 1, 0)
|
|
|| test_gemm_int8(M, N, K, 1.3f, 1, 1, 0, 0, 1, 1, 1)
|
|
|| test_gemm_int8(M, N, K, 1.4f, 0, 0, 0, 0, 1, 0, 0)
|
|
|| test_gemm_int8(M, N, K, 1.5f, 1, 0, 0, 0, 1, 0, 1)
|
|
|
|
|| test_gemm_int8(M, N, K, -1.2f, 0, 1, 0, 1, 1, 1, 0)
|
|
|| test_gemm_int8(M, N, K, -1.3f, 1, 1, 0, 1, 1, 1, 0)
|
|
|| test_gemm_int8(M, N, K, -1.4f, 0, 0, 0, 1, 1, 1, 1)
|
|
|| test_gemm_int8(M, N, K, -1.5f, 1, 0, 0, 1, 1, 1, 1)
|
|
|
|
|| test_gemm_int8(M, N, K, -2.0f, 0, 1, 0, 1, 0, 1, 1)
|
|
|| test_gemm_int8(M, N, K, -3.0f, 1, 1, 0, 1, 0, 1, 1)
|
|
|| test_gemm_int8(M, N, K, -4.0f, 0, 0, 0, 1, 1, 0, 0)
|
|
|| test_gemm_int8(M, N, K, -5.0f, 0, 1, 0, 1, 1, 0, 0)
|
|
|
|
|| test_gemm_int8(M, N, K, -2.1f, 0, 1, 0, 1, 0, 0, 0)
|
|
|| test_gemm_int8(M, N, K, -3.1f, 1, 1, 0, 1, 0, 0, 1)
|
|
|| test_gemm_int8(M, N, K, -4.1f, 0, 0, 0, 1, 0, 1, 0)
|
|
|| test_gemm_int8(M, N, K, -5.1f, 1, 0, 0, 1, 0, 1, 1)
|
|
|
|
|| test_gemm_int8_fp16s(M, N, K, 1.f, 0, 1, 0, 0, 0, 0, 0)
|
|
|| test_gemm_int8_fp16s(M, N, K, 1.f, 1, 0, 0, 1, 0, 0, 0);
|
|
}
|
|
|
|
static int test_gemm_1(int M, int N, int K)
|
|
{
|
|
return 0
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(1), 2.1f, 0.5f, 0, 0, 0, 0, 0, 0, 0)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(1), 2.1f, 0.5f, 0, 0, 1, 1, 0, 0, 0)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(M), 3.1f, 0.6f, 0, 1, 2, 0, 0, 0, 0)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(M), 3.1f, 0.6f, 0, 1, 3, 1, 0, 0, 0)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(1, M), 4.1f, 0.7f, 1, 0, 0, 0, 0, 0, 0)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(1, M), 4.1f, 0.7f, 1, 0, 1, 1, 0, 0, 0)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N, M), 5.1f, -0.8f, 1, 1, 2, 0, 0, 0, 0)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N, M), 5.1f, -0.8f, 1, 1, 3, 1, 0, 0, 0)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N, M), 1.f, 1.f, 1, 1, 0, 0, 0, 0, 0)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N, M), 1.f, 1.f, 1, 1, 1, 1, 0, 0, 0)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N, 1), 2.1f, -0.5f, 0, 0, 2, 0, 0, 0, 0)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N, 1), 2.1f, -0.5f, 0, 0, 3, 1, 0, 0, 0)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N, 1), 0.8f, 1.f, 0, 0, 0, 0, 0, 0, 0)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N), 0.8f, 1.f, 0, 0, 1, 1, 0, 0, 0)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N), 3.1f, -0.6f, 0, 1, 2, 0, 0, 0, 0)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N), 3.1f, -0.6f, 0, 1, 3, 1, 0, 0, 0)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(1), 1.7f, -0.4f, 0, 0, 0, 0, 0, 0, 0, false, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(M), -1.3f, 0.6f, 1, 0, 0, 1, 0, 0, 0, false, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N, M), 0.8f, 0.5f, 0, 1, 0, 0, 0, 0, 0, false, 1)
|
|
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(1), -2.1f, 0.5f, 0, 0, 0, 0, 1, 1, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(1), -2.1f, 0.5f, 0, 0, 1, 1, 1, 1, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(M), -3.1f, 0.6f, 0, 1, 2, 0, 1, 1, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(M), -3.1f, 0.6f, 0, 1, 3, 1, 1, 1, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(1, M), -4.1f, 0.7f, 1, 0, 0, 0, 1, 1, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(1, M), -4.1f, 0.7f, 1, 0, 1, 1, 1, 1, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N, M), -5.1f, -0.8f, 1, 1, 2, 0, 1, 1, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N, M), -5.1f, -0.8f, 1, 1, 3, 1, 1, 1, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N, M), 1.f, 1.f, 1, 1, 0, 0, 1, 1, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N, M), 1.f, 1.f, 1, 1, 1, 1, 1, 1, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N, 1), -2.1f, -0.5f, 0, 0, 2, 0, 1, 1, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N, 1), -2.1f, -0.5f, 0, 0, 3, 1, 1, 1, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N, 1), 0.8f, 1.f, 0, 0, 0, 0, 1, 1, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N), 0.8f, 1.f, 0, 0, 1, 1, 1, 1, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N), -3.1f, -0.6f, 0, 1, 2, 0, 1, 1, 1)
|
|
|| test_gemm_int8_bias(M, N, K, RandomMat(N), -3.1f, -0.6f, 0, 1, 3, 1, 1, 1, 1);
|
|
}
|
|
#endif // NCNN_INT8
|
|
|
|
int main()
|
|
{
|
|
SRAND(7767517);
|
|
|
|
#if NCNN_INT8
|
|
int mnk[][3] = {
|
|
{1, 1, 1},
|
|
{1, 1, 23},
|
|
{1, 1, 47},
|
|
{1, 23, 1},
|
|
{1, 23, 23},
|
|
{1, 31, 1},
|
|
{1, 35, 1},
|
|
{1, 35, 47},
|
|
{1, 47, 1},
|
|
{2, 2, 2},
|
|
{3, 3, 3},
|
|
{4, 4, 4},
|
|
{5, 5, 5},
|
|
{6, 6, 6},
|
|
{7, 7, 7},
|
|
{7, 31, 3},
|
|
{8, 8, 8},
|
|
{12, 12, 23},
|
|
{12, 23, 12},
|
|
{12, 31, 12},
|
|
{15, 15, 15},
|
|
{16, 16, 16},
|
|
{19, 44, 7},
|
|
{20, 28, 7},
|
|
{23, 31, 1},
|
|
{23, 31, 23},
|
|
{24, 24, 47},
|
|
{24, 35, 24},
|
|
{24, 47, 24},
|
|
{31, 31, 31},
|
|
{32, 32, 9},
|
|
{35, 47, 48},
|
|
{35, 48, 47},
|
|
{40, 40, 40},
|
|
{47, 48, 47}
|
|
};
|
|
|
|
int mnk_count = sizeof(mnk) / sizeof(int) / 3;
|
|
|
|
for (int i = 0; i < mnk_count; i++)
|
|
{
|
|
int M = mnk[i][0];
|
|
int N = mnk[i][1];
|
|
int K = mnk[i][2];
|
|
|
|
int ret = test_gemm_0(M, N, K) || test_gemm_1(M, N, K);
|
|
if (ret != 0)
|
|
return ret;
|
|
|
|
if (M != N)
|
|
{
|
|
int ret = test_gemm_0(N, M, K) || test_gemm_1(N, M, K);
|
|
if (ret != 0)
|
|
return ret;
|
|
}
|
|
}
|
|
|
|
if (test_gemm_int8_bf16s(12, 23, 12, 1.f, 0, 1, 0, 0, 0, 0, 0)
|
|
|| test_gemm_int8_bf16s(12, 23, 12, 1.f, 1, 0, 0, 1, 0, 0, 0)
|
|
|| test_gemm_int8_bias(12, 23, 12, RandomMat(23), 1.7f, -0.4f, 0, 1, 0, 1, 0, 0, 0, true))
|
|
{
|
|
return -1;
|
|
}
|
|
#else
|
|
// test nothing for non-int8 build
|
|
#endif
|
|
|
|
return 0;
|
|
}
|