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提交 fa488338 编写于 作者: M Megvii Engine Team
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feat(dnn,imperative): remove the restriction of tensor shape when using uint8 region mask 

GitOrigin-RevId: 37d99006978d756d22111347be2ab2d895f71661
上级 cdf7baa2
隐藏空白更改
内联 并排
Showing with 258 addition and 142 deletion
dnn/src/cuda/region_restricted_convolution/chanwise/depthwise_large_filter_algo.cuh
浏览文件 @ fa488338
......@@ -784,20 +784,24 @@ __global__ void DepthwiseConv2dGPUKernelNCHW(
static_assert((OutTileConfig::unroll_w & 3) == 0, "output tile unroll_w & 3 != 0");
static_assert((OutTileConfig::block_w & 3) == 0, "output block_w & 3 != 0");
int reg_rout[OutTileConfig::unroll_size] = {0};
int relative_offset = sizeof(dt_int32) / sizeof(dt_uint8);
#pragma unroll
for (int i = 0; i < OutTileConfig::unroll_h; ++i) {
int out_h_idx = out_base_h_idx + i;
if (out_h_idx < param.out_h) {
#pragma unroll
for (int j = 0; j < OutTileConfig::unroll_w; j += 4) {
for (int j = 0; j < OutTileConfig::unroll_w; j += relative_offset) {
int out_w_idx = out_start_w + j;
if (out_w_idx < param.out_w) {
uint32_t val = *(reinterpret_cast<const uint32_t*>(
&rout_base_ptr[out_h_idx * param.out_w + out_w_idx]));
reg_rout[i * OutTileConfig::unroll_w + j] = val & 0xff;
reg_rout[i * OutTileConfig::unroll_w + j + 1] = (val >> 8) & 0xff;
reg_rout[i * OutTileConfig::unroll_w + j + 2] = (val >> 16) & 0xff;
reg_rout[i * OutTileConfig::unroll_w + j + 3] = (val >> 24) & 0xff;
int valid_offset = relative_offset + out_w_idx > param.out_w
? param.out_w - out_w_idx
: relative_offset;
#pragma unroll
for (int t = 0; t < valid_offset; t += 1) {
uint8_t val =
rout_base_ptr[out_h_idx * param.out_w + out_w_idx + t];
reg_rout[i * OutTileConfig::unroll_w + j + t] = val & 0xff;
}
}
}
}
......@@ -855,21 +859,23 @@ __global__ void DepthwiseConv2dGPUKernelNCHW(
int s_idx = (off_oh * stride_h + s_h) % SrcTileCount::smem_h *
SrcTileCount::smem_w +
(off_oh * stride_h + s_h) / SrcTileCount::bank_offset_line;
int r_idx = (off_oh * stride_h + s_h) % RinTileCount::smem_h *
RinTileCount::smem_w +
(off_oh * stride_h + s_h) / RinTileCount::bank_offset_line;
#pragma unroll
for (int s_w = 0; s_w < irin_unroll_w; s_w += 4) {
uint32_t val = smem_rin_ptr
[(off_oh * stride_h + s_h) % RinTileCount::smem_h *
RinTileCount::smem_w +
(s_w >> 2) +
(off_oh * stride_h + s_h) / RinTileCount::bank_offset_line];
reg_src[0][s_h * irin_unroll_w + s_w] = smem_src_ptr[s_idx + s_w];
reg_src[0][s_h * irin_unroll_w + s_w + 1] = smem_src_ptr[s_idx + s_w + 1];
reg_src[0][s_h * irin_unroll_w + s_w + 2] = smem_src_ptr[s_idx + s_w + 2];
reg_src[0][s_h * irin_unroll_w + s_w + 3] = smem_src_ptr[s_idx + s_w + 3];
reg_rin[0][s_h * irin_unroll_w + s_w] = val & 0xff;
reg_rin[0][s_h * irin_unroll_w + s_w + 1] = (val >> 8) & 0xff;
reg_rin[0][s_h * irin_unroll_w + s_w + 2] = (val >> 16) & 0xff;
reg_rin[0][s_h * irin_unroll_w + s_w + 3] = (val >> 24) & 0xff;
for (int s_w = 0; s_w < SrcTileConfig::unroll_w; ++s_w) {
reg_src[0][s_h * SrcTileConfig::unroll_w + s_w] = smem_src_ptr[s_idx + s_w];
}
#pragma unroll
for (int s_w = 0; s_w < irin_unroll_w; s_w += relative_offset) {
reg_rin[0][s_h * irin_unroll_w + s_w] =
(smem_rin_ptr[r_idx + (s_w >> 2)]) & 0xff;
reg_rin[0][s_h * irin_unroll_w + s_w + 1] =
(smem_rin_ptr[r_idx + (s_w >> 2)] >> 8) & 0xff;
reg_rin[0][s_h * irin_unroll_w + s_w + 2] =
(smem_rin_ptr[r_idx + (s_w >> 2)] >> 16) & 0xff;
reg_rin[0][s_h * irin_unroll_w + s_w + 3] =
(smem_rin_ptr[r_idx + (s_w >> 2)] >> 24) & 0xff;
}
}
......@@ -1108,6 +1114,7 @@ void LaunchDepthwiseConv2dGPU(
if (param.is_compute_deafult) {
kernel = DepthwiseConv2dGPUKernelNCHW<IConvTrait, kDirection, stride>;
} else {
printf("expected dnn param compute default mode\n");
megdnn_assert_internal(0);
}
if (is_fwd) {
......
dnn/src/cuda/region_restricted_convolution/opr_impl.cpp
浏览文件 @ fa488338
......@@ -25,9 +25,6 @@ void RegionRestrictedConvolutionForwardImpl::exec(
fm.spatial_ndim == 2 && fm.icpg == 1 && fm.ocpg == 1 &&
fm.dilation[0] == 1 && fm.dilation[1] == 1 && !fm.should_flip &&
param().stride_h == 1 && param().stride_w == 1);
if (rin.layout.dtype == dtype::Uint8()) {
megdnn_assert((src.layout.shape[3] & 3) == 0 && (dst.layout.shape[3] & 3) == 0);
}
auto stream = cuda_stream(handle());
......@@ -43,6 +40,7 @@ void RegionRestrictedConvolutionForwardImpl::exec(
dst.ptr<float>(), src.ptr<float>(), filter.ptr<float>(),
rin.ptr<uint8_t>(), rout.ptr<uint8_t>(), kparam, stream);
} else {
printf("unexpected region restricted conv mode\n");
megdnn_assert_internal(0);
}
}
......@@ -81,11 +79,6 @@ void RegionRestrictedConvolutionBackwardDataImpl::exec(
fm.spatial_ndim == 2 && fm.icpg == 1 && fm.ocpg == 1 &&
fm.dilation[0] == 1 && fm.dilation[1] == 1 && !fm.should_flip &&
param().stride_h == 1 && param().stride_w == 1);
// NOTE: uint8 dtype region mask requires the spatial size of src&dst is 4*N
if (rin.layout.dtype == dtype::Uint8()) {
megdnn_assert(
(grad.layout.shape[3] & 3) == 0 && (diff.layout.shape[3] & 3) == 0);
}
auto stream = cuda_stream(handle());
if (filter.layout.dtype == dtype::Float32() && rin.layout.dtype == dtype::Int32() &&
rout.layout.dtype == dtype::Int32()) {
......@@ -135,8 +128,6 @@ void RegionRestrictedConvolutionBackwardFilterImpl::exec(
int ph = fm.padding[0], pw = fm.padding[1];
int dh = 0, dw = 0;
// check if channelwise convolution
megdnn_assert(fm.icpg == 1 && fm.ocpg == 1);
auto stream = cuda_stream(handle());
float alpha = 1.f;
......
dnn/test/cuda/region_restricted_convolution.cpp
浏览文件 @ fa488338
#include "megdnn/dtype.h"
#include "megdnn/opr_param_defs.h"
#include "megdnn/oprs.h"
#include "megdnn/oprs/nn.h"
#include "test/common/checker.h"
#include "test/common/conv_bias.h"
#include "test/common/rng.h"
......@@ -11,6 +12,7 @@
#include "test/cuda/utils.h"
#include <cudnn.h>
#include <gtest/gtest.h>
#define V1(x) #x
#define V(x) V1(x)
......@@ -37,9 +39,6 @@ TEST_F(CUDA, REGION_RESTRICTED_CONV_FORWARD_LARGE_FILTER) {
UniformIntRNG r_rng{0, 2};
checker.set_rng(0, &rng).set_rng(1, &rng).set_rng(2, &r_rng).set_rng(
3, &r_rng);
if (dt.enumv() == DTypeEnum::Float16) {
checker.set_epsilon(1e-1);
}
cur_param.pad_h = cur_param.pad_w = padding;
cur_param.stride_h = cur_param.stride_w = stride;
......@@ -49,11 +48,32 @@ TEST_F(CUDA, REGION_RESTRICTED_CONV_FORWARD_LARGE_FILTER) {
checker.set_param(cur_param).execs(
{{n, g, h, h}, {g, 1, 1, fh, fh}, {n, h, h}, {n, ho, ho}, {}});
};
run(1, 1, 3, 2, 1, 1);
run(1, 1, 5, 2, 1, 1);
run(1, 1, 6, 2, 1, 1);
run(1, 1, 7, 2, 1, 1);
run(1, 1, 9, 2, 1, 1);
run(1, 1, 10, 2, 1, 1);
run(1, 1, 11, 2, 1, 1);
run(1, 1, 13, 2, 1, 1);
run(1, 1, 14, 2, 1, 1);
run(1, 1, 15, 2, 1, 1);
run(1, 1, 17, 2, 1, 1);
run(1, 1, 18, 2, 1, 1);
run(1, 1, 19, 2, 1, 1);
run(1, 1, 21, 2, 1, 1);
run(1, 1, 22, 2, 1, 1);
run(1, 1, 23, 2, 1, 1);
run(1, 1, 25, 2, 1, 1);
run(1, 1, 26, 2, 1, 1);
run(1, 1, 27, 2, 1, 1);
run(1, 1, 29, 2, 1, 1);
run(1, 1, 30, 2, 1, 1);
run(1, 1, 31, 2, 1, 1);
run(4, 8, 32, 3, 3 / 2, 1);
run(4, 8, 32, 5, 5 / 2, 1);
run(4, 8, 32, 7, 7 / 2, 1);
run(1, 2, 32, 9, 9 / 2, 1);
run(4, 1, 32, 9, 9 / 2, 1);
run(4, 8, 32, 9, 9 / 2, 1);
run(4, 8, 32, 11, 11 / 2, 1);
run(4, 8, 32, 13, 13 / 2, 1);
run(4, 8, 32, 15, 15 / 2, 1);
......@@ -65,12 +85,27 @@ TEST_F(CUDA, REGION_RESTRICTED_CONV_FORWARD_LARGE_FILTER) {
run(4, 8, 32, 27, 27 / 2, 1);
run(4, 8, 32, 29, 29 / 2, 1);
run(4, 8, 32, 31, 31 / 2, 1);
run(4, 8, 31, 3, 3 / 2, 1);
run(4, 8, 31, 5, 5 / 2, 1);
run(4, 8, 31, 7, 7 / 2, 1);
run(4, 8, 31, 9, 9 / 2, 1);
run(4, 8, 31, 11, 11 / 2, 1);
run(4, 8, 31, 13, 13 / 2, 1);
run(4, 8, 31, 15, 15 / 2, 1);
run(4, 8, 31, 17, 17 / 2, 1);
run(4, 8, 31, 19, 19 / 2, 1);
run(4, 8, 31, 21, 21 / 2, 1);
run(4, 8, 31, 23, 23 / 2, 1);
run(4, 8, 31, 25, 25 / 2, 1);
run(4, 8, 31, 27, 27 / 2, 1);
run(4, 8, 31, 29, 29 / 2, 1);
run(4, 8, 31, 31, 31 / 2, 1);
}
}
#if MEGDNN_WITH_BENCHMARK
TEST_F(CUDA, BENCHMARK_REGION_RESTRICTED_CONV_FORWARD_LARGE_FILTER_FP32) {
TEST_F(CUDA, BENCHMARK_REGION_RESTRICTED_CONV_FORWARD_LARGE_FILTER_FP32_INT32) {
require_compute_capability(7, 5);
Benchmarker<ConvBiasForward> bencher(handle_cuda());
bencher.set_display(false);
......@@ -153,24 +188,24 @@ TEST_F(CUDA, BENCHMARK_REGION_RESTRICTED_CONV_FORWARD_LARGE_FILTER_FP32) {
time_in_ms / rr_time_in_ms);
};
run_bench(64, 384, 32, 32, 3, 3, 1, 1, 10);
run_bench(64, 384, 32, 32, 5, 5, 1, 1, 10);
run_bench(64, 384, 32, 32, 7, 7, 1, 1, 10);
run_bench(64, 384, 32, 32, 9, 9, 1, 1, 10);
run_bench(64, 384, 32, 32, 11, 11, 1, 1, 10);
run_bench(64, 384, 32, 32, 13, 13, 1, 1, 10);
run_bench(64, 384, 32, 32, 15, 15, 1, 1, 10);
run_bench(64, 384, 32, 32, 17, 17, 1, 1, 10);
run_bench(64, 384, 32, 32, 19, 19, 1, 1, 10);
run_bench(64, 384, 32, 32, 21, 21, 1, 1, 10);
run_bench(64, 384, 32, 32, 23, 23, 1, 1, 10);
run_bench(64, 384, 32, 32, 25, 25, 1, 1, 10);
run_bench(64, 384, 32, 32, 27, 27, 1, 1, 10);
run_bench(64, 384, 32, 32, 29, 29, 1, 1, 10);
run_bench(64, 384, 32, 32, 31, 31, 1, 1, 10);
run_bench(64, 384, 32, 32, 3, 3, 1, 1, 1000);
run_bench(64, 384, 32, 32, 5, 5, 1, 1, 1000);
run_bench(64, 384, 32, 32, 7, 7, 1, 1, 1000);
run_bench(64, 384, 32, 32, 9, 9, 1, 1, 1000);
run_bench(64, 384, 32, 32, 11, 11, 1, 1, 1000);
run_bench(64, 384, 32, 32, 13, 13, 1, 1, 1000);
run_bench(64, 384, 32, 32, 15, 15, 1, 1, 1000);
run_bench(64, 384, 32, 32, 17, 17, 1, 1, 1000);
run_bench(64, 384, 32, 32, 19, 19, 1, 1, 1000);
run_bench(64, 384, 32, 32, 21, 21, 1, 1, 1000);
run_bench(64, 384, 32, 32, 23, 23, 1, 1, 1000);
run_bench(64, 384, 32, 32, 25, 25, 1, 1, 1000);
run_bench(64, 384, 32, 32, 27, 27, 1, 1, 1000);
run_bench(64, 384, 32, 32, 29, 29, 1, 1, 1000);
run_bench(64, 384, 32, 32, 31, 31, 1, 1, 1000);
}
TEST_F(CUDA, BENCHMARK_REGION_RESTRICTED_CONV_BACKWARD_LARGE_FILTER_FP32) {
TEST_F(CUDA, BENCHMARK_REGION_RESTRICTED_CONV_BACKWARD_DATA_FP32_INT32) {
require_compute_capability(7, 5);
Benchmarker<ConvolutionBackwardData> bencher(handle_cuda());
bencher.set_display(false);
......@@ -251,24 +286,24 @@ TEST_F(CUDA, BENCHMARK_REGION_RESTRICTED_CONV_BACKWARD_LARGE_FILTER_FP32) {
time_in_ms / rr_time_in_ms);
};
run_bench(64, 384, 32, 32, 3, 3, 1, 1, 10);
run_bench(64, 384, 32, 32, 5, 5, 1, 1, 10);
run_bench(64, 384, 32, 32, 7, 7, 1, 1, 10);
run_bench(64, 384, 32, 32, 9, 9, 1, 1, 10);
run_bench(64, 384, 32, 32, 11, 11, 1, 1, 10);
run_bench(64, 384, 32, 32, 13, 13, 1, 1, 10);
run_bench(64, 384, 32, 32, 15, 15, 1, 1, 10);
run_bench(64, 384, 32, 32, 17, 17, 1, 1, 10);
run_bench(64, 384, 32, 32, 19, 19, 1, 1, 10);
run_bench(64, 384, 32, 32, 21, 21, 1, 1, 10);
run_bench(64, 384, 32, 32, 23, 23, 1, 1, 10);
run_bench(64, 384, 32, 32, 25, 25, 1, 1, 10);
run_bench(64, 384, 32, 32, 27, 27, 1, 1, 10);
run_bench(64, 384, 32, 32, 29, 29, 1, 1, 10);
run_bench(64, 384, 32, 32, 31, 31, 1, 1, 10);
run_bench(64, 384, 32, 32, 3, 3, 1, 1, 1000);
run_bench(64, 384, 32, 32, 5, 5, 1, 1, 1000);
run_bench(64, 384, 32, 32, 7, 7, 1, 1, 1000);
run_bench(64, 384, 32, 32, 9, 9, 1, 1, 1000);
run_bench(64, 384, 32, 32, 11, 11, 1, 1, 1000);
run_bench(64, 384, 32, 32, 13, 13, 1, 1, 1000);
run_bench(64, 384, 32, 32, 15, 15, 1, 1, 1000);
run_bench(64, 384, 32, 32, 17, 17, 1, 1, 1000);
run_bench(64, 384, 32, 32, 19, 19, 1, 1, 1000);
run_bench(64, 384, 32, 32, 21, 21, 1, 1, 1000);
run_bench(64, 384, 32, 32, 23, 23, 1, 1, 1000);
run_bench(64, 384, 32, 32, 25, 25, 1, 1, 1000);
run_bench(64, 384, 32, 32, 27, 27, 1, 1, 1000);
run_bench(64, 384, 32, 32, 29, 29, 1, 1, 1000);
run_bench(64, 384, 32, 32, 31, 31, 1, 1, 1000);
}
TEST_F(CUDA, BENCHMARK_REGION_RESTRICTED_CONV_BACKWARD_LARGE_FILTER_FP32_UINT8) {
TEST_F(CUDA, BENCHMARK_REGION_RESTRICTED_CONV_BACKWARD_DATA_FP32_UINT8) {
require_compute_capability(7, 5);
Benchmarker<ConvolutionBackwardData> bencher(handle_cuda());
bencher.set_display(false);
......@@ -349,21 +384,36 @@ TEST_F(CUDA, BENCHMARK_REGION_RESTRICTED_CONV_BACKWARD_LARGE_FILTER_FP32_UINT8)
time_in_ms / rr_time_in_ms);
};
run_bench(64, 384, 32, 32, 3, 3, 1, 1, 10);
run_bench(64, 384, 32, 32, 5, 5, 1, 1, 10);
run_bench(64, 384, 32, 32, 7, 7, 1, 1, 10);
run_bench(64, 384, 32, 32, 9, 9, 1, 1, 10);
run_bench(64, 384, 32, 32, 11, 11, 1, 1, 10);
run_bench(64, 384, 32, 32, 13, 13, 1, 1, 10);
run_bench(64, 384, 32, 32, 15, 15, 1, 1, 10);
run_bench(64, 384, 32, 32, 17, 17, 1, 1, 10);
run_bench(64, 384, 32, 32, 19, 19, 1, 1, 10);
run_bench(64, 384, 32, 32, 21, 21, 1, 1, 10);
run_bench(64, 384, 32, 32, 23, 23, 1, 1, 10);
run_bench(64, 384, 32, 32, 25, 25, 1, 1, 10);
run_bench(64, 384, 32, 32, 27, 27, 1, 1, 10);
run_bench(64, 384, 32, 32, 29, 29, 1, 1, 10);
run_bench(64, 384, 32, 32, 31, 31, 1, 1, 10);
run_bench(64, 384, 32, 32, 3, 3, 1, 1, 1000);
run_bench(64, 384, 32, 32, 5, 5, 1, 1, 1000);
run_bench(64, 384, 32, 32, 7, 7, 1, 1, 1000);
run_bench(64, 384, 32, 32, 9, 9, 1, 1, 1000);
run_bench(64, 384, 32, 32, 11, 11, 1, 1, 1000);
run_bench(64, 384, 32, 32, 13, 13, 1, 1, 1000);
run_bench(64, 384, 32, 32, 15, 15, 1, 1, 1000);
run_bench(64, 384, 32, 32, 17, 17, 1, 1, 1000);
run_bench(64, 384, 32, 32, 19, 19, 1, 1, 1000);
run_bench(64, 384, 32, 32, 21, 21, 1, 1, 1000);
run_bench(64, 384, 32, 32, 23, 23, 1, 1, 1000);
run_bench(64, 384, 32, 32, 25, 25, 1, 1, 1000);
run_bench(64, 384, 32, 32, 27, 27, 1, 1, 1000);
run_bench(64, 384, 32, 32, 29, 29, 1, 1, 1000);
run_bench(64, 384, 32, 32, 31, 31, 1, 1, 1000);
run_bench(64, 384, 31, 31, 3, 3, 1, 1, 1000);
run_bench(64, 384, 31, 31, 5, 5, 1, 1, 1000);
run_bench(64, 384, 31, 31, 7, 7, 1, 1, 1000);
run_bench(64, 384, 31, 31, 9, 9, 1, 1, 1000);
run_bench(64, 384, 31, 31, 11, 11, 1, 1, 1000);
run_bench(64, 384, 31, 31, 13, 13, 1, 1, 1000);
run_bench(64, 384, 31, 31, 15, 15, 1, 1, 1000);
run_bench(64, 384, 31, 31, 17, 17, 1, 1, 1000);
run_bench(64, 384, 31, 31, 19, 19, 1, 1, 1000);
run_bench(64, 384, 31, 31, 21, 21, 1, 1, 1000);
run_bench(64, 384, 31, 31, 23, 23, 1, 1, 1000);
run_bench(64, 384, 31, 31, 25, 25, 1, 1, 1000);
run_bench(64, 384, 31, 31, 27, 27, 1, 1, 1000);
run_bench(64, 384, 31, 31, 29, 29, 1, 1, 1000);
run_bench(64, 384, 31, 31, 31, 31, 1, 1, 1000);
}
TEST_F(CUDA, BENCHMARK_REGION_RESTRICTED_CONV_FORWARD_LARGE_FILTER_UINT8) {
......@@ -449,21 +499,36 @@ TEST_F(CUDA, BENCHMARK_REGION_RESTRICTED_CONV_FORWARD_LARGE_FILTER_UINT8) {
time_in_ms / rr_time_in_ms);
};
run_bench(64, 384, 32, 32, 3, 3, 1, 1, 10);
run_bench(64, 384, 32, 32, 5, 5, 1, 1, 10);
run_bench(64, 384, 32, 32, 7, 7, 1, 1, 10);
run_bench(64, 384, 32, 32, 9, 9, 1, 1, 10);
run_bench(64, 384, 32, 32, 11, 11, 1, 1, 10);
run_bench(64, 384, 32, 32, 13, 13, 1, 1, 10);
run_bench(64, 384, 32, 32, 15, 15, 1, 1, 10);
run_bench(64, 384, 32, 32, 17, 17, 1, 1, 10);
run_bench(64, 384, 32, 32, 19, 19, 1, 1, 10);
run_bench(64, 384, 32, 32, 21, 21, 1, 1, 10);
run_bench(64, 384, 32, 32, 23, 23, 1, 1, 10);
run_bench(64, 384, 32, 32, 25, 25, 1, 1, 10);
run_bench(64, 384, 32, 32, 27, 27, 1, 1, 10);
run_bench(64, 384, 32, 32, 29, 29, 1, 1, 10);
run_bench(64, 384, 32, 32, 31, 31, 1, 1, 10);
run_bench(64, 384, 32, 32, 3, 3, 1, 1, 1000);
run_bench(64, 384, 32, 32, 5, 5, 1, 1, 1000);
run_bench(64, 384, 32, 32, 7, 7, 1, 1, 1000);
run_bench(64, 384, 32, 32, 9, 9, 1, 1, 1000);
run_bench(64, 384, 32, 32, 11, 11, 1, 1, 1000);
run_bench(64, 384, 32, 32, 13, 13, 1, 1, 1000);
run_bench(64, 384, 32, 32, 15, 15, 1, 1, 1000);
run_bench(64, 384, 32, 32, 17, 17, 1, 1, 1000);
run_bench(64, 384, 32, 32, 19, 19, 1, 1, 1000);
run_bench(64, 384, 32, 32, 21, 21, 1, 1, 1000);
run_bench(64, 384, 32, 32, 23, 23, 1, 1, 1000);
run_bench(64, 384, 32, 32, 25, 25, 1, 1, 1000);
run_bench(64, 384, 32, 32, 27, 27, 1, 1, 1000);
run_bench(64, 384, 32, 32, 29, 29, 1, 1, 1000);
run_bench(64, 384, 32, 32, 31, 31, 1, 1, 1000);
run_bench(64, 384, 31, 31, 3, 3, 1, 1, 1000);
run_bench(64, 384, 31, 31, 5, 5, 1, 1, 1000);
run_bench(64, 384, 31, 31, 7, 7, 1, 1, 1000);
run_bench(64, 384, 31, 31, 9, 9, 1, 1, 1000);
run_bench(64, 384, 31, 31, 11, 11, 1, 1, 1000);
run_bench(64, 384, 31, 31, 13, 13, 1, 1, 1000);
run_bench(64, 384, 31, 31, 15, 15, 1, 1, 1000);
run_bench(64, 384, 31, 31, 17, 17, 1, 1, 1000);
run_bench(64, 384, 31, 31, 19, 19, 1, 1, 1000);
run_bench(64, 384, 31, 31, 21, 21, 1, 1, 1000);
run_bench(64, 384, 31, 31, 23, 23, 1, 1, 1000);
run_bench(64, 384, 31, 31, 25, 25, 1, 1, 1000);
run_bench(64, 384, 31, 31, 27, 27, 1, 1, 1000);
run_bench(64, 384, 31, 31, 29, 29, 1, 1, 1000);
run_bench(64, 384, 31, 31, 31, 31, 1, 1, 1000);
}
TEST_F(CUDA, BENCHMARK_REGION_RESTRICTED_CONV_BACKWARD_FILTER_FP32) {
......@@ -538,7 +603,7 @@ TEST_F(CUDA, BENCHMARK_REGION_RESTRICTED_CONV_BACKWARD_FILTER_FP32) {
auto rr_time_in_ms = rr_bencher.execs({src, diff, rin, rout, grad}) / nr_times;
auto rr_ops =
2.0 * batch * g * hi * wi * fh * fw / (rr_time_in_ms * 1e-3) * 1e-12;
printf("[DGRAD]RegionRestrictedDepthwiseLargeFilter vs DepthwiseLargeFilter: "
printf("[WGRAD]RegionRestrictedDepthwiseLargeFilter vs DepthwiseLargeFilter: "
"src=%s, "
"diff=%s, grad=%s\n"
"time: %.2f ms, time(rr): %.2f ms, perf: %.2fTops, perf(rr): %.2f Tops\n"
......@@ -638,7 +703,7 @@ TEST_F(CUDA, BENCHMARK_REGION_RESTRICTED_CONV_BACKWARD_FILTER_FP32_RINT8) {
auto rr_time_in_ms = rr_bencher.execs({src, diff, rin, rout, grad}) / nr_times;
auto rr_ops =
2.0 * batch * g * hi * wi * fh * fw / (rr_time_in_ms * 1e-3) * 1e-12;
printf("[DGRAD]RegionRestrictedDepthwiseLargeFilter vs DepthwiseLargeFilter: "
printf("[WGRAD]RegionRestrictedDepthwiseLargeFilter vs DepthwiseLargeFilter: "
"src=%s, "
"diff=%s, grad=%s\n"
"time: %.2f ms, time(rr): %.2f ms, perf: %.2fTops, perf(rr): %.2f Tops\n"
......@@ -703,15 +768,30 @@ TEST_F(CUDA, REGION_RESTRICTED_CONV_BWD_DATA_FP32) {
{n, g * 1, ih, ih} // grad
});
};
if (dt == dtype::Int32()) {
run(4, 8, 32, 5, 5 / 2, 1);
run(1, 2, 2, 2, 0, 1);
run(1, 2, 3, 3, 0, 1);
run(1, 2, 4, 4, 0, 1);
run(1, 2, 5, 5, 0, 1);
run(1, 2, 6, 6, 0, 1);
run(1, 2, 7, 7, 0, 1);
}
run(1, 1, 3, 2, 1, 1);
run(1, 1, 5, 2, 1, 1);
run(1, 1, 6, 2, 1, 1);
run(1, 1, 7, 2, 1, 1);
run(1, 1, 9, 2, 1, 1);
run(1, 1, 10, 2, 1, 1);
run(1, 1, 11, 2, 1, 1);
run(1, 1, 13, 2, 1, 1);
run(1, 1, 14, 2, 1, 1);
run(1, 1, 15, 2, 1, 1);
run(1, 1, 17, 2, 1, 1);
run(1, 1, 18, 2, 1, 1);
run(1, 1, 19, 2, 1, 1);
run(1, 1, 21, 2, 1, 1);
run(1, 1, 22, 2, 1, 1);
run(1, 1, 23, 2, 1, 1);
run(1, 1, 25, 2, 1, 1);
run(1, 1, 26, 2, 1, 1);
run(1, 1, 27, 2, 1, 1);
run(1, 1, 29, 2, 1, 1);
run(1, 1, 30, 2, 1, 1);
run(1, 1, 31, 2, 1, 1);
run(4, 8, 32, 3, 3 / 2, 1);
run(4, 8, 32, 5, 5 / 2, 1);
run(4, 8, 32, 7, 7 / 2, 1);
run(4, 8, 32, 9, 9 / 2, 1);
run(4, 8, 32, 11, 11 / 2, 1);
......@@ -724,8 +804,22 @@ TEST_F(CUDA, REGION_RESTRICTED_CONV_BWD_DATA_FP32) {
run(4, 8, 32, 25, 25 / 2, 1);
run(4, 8, 32, 27, 27 / 2, 1);
run(4, 8, 32, 29, 29 / 2, 1);
run(4, 1, 32, 29, 29 / 2, 1);
run(4, 8, 32, 31, 31 / 2, 1);
run(4, 8, 31, 3, 3 / 2, 1);
run(4, 8, 31, 5, 5 / 2, 1);
run(4, 8, 31, 7, 7 / 2, 1);
run(4, 8, 31, 9, 9 / 2, 1);
run(4, 8, 31, 11, 11 / 2, 1);
run(4, 8, 31, 13, 13 / 2, 1);
run(4, 8, 31, 15, 15 / 2, 1);
run(4, 8, 31, 17, 17 / 2, 1);
run(4, 8, 31, 19, 19 / 2, 1);
run(4, 8, 31, 21, 21 / 2, 1);
run(4, 8, 31, 23, 23 / 2, 1);
run(4, 8, 31, 25, 25 / 2, 1);
run(4, 8, 31, 27, 27 / 2, 1);
run(4, 8, 31, 29, 29 / 2, 1);
run(4, 8, 31, 31, 31 / 2, 1);
}
}
......@@ -761,16 +855,30 @@ TEST_F(CUDA, REGION_RESTRICTED_CONV_BWD_DATA_FP32_RIN_EQ_ROUT) {
/*rout*/ {n, oh, oh},
/*grad*/ {n, g * 1, ih, ih}});
};
if (dt == dtype::Int32()) {
// NOTE: UINT8 assert the spatial size of src&dst is 4*N
run(4, 8, 32, 5, 5 / 2, 1);
run(1, 2, 2, 2, 0, 1);
run(1, 2, 3, 3, 0, 1);
run(1, 2, 4, 4, 0, 1);
run(1, 2, 5, 5, 0, 1);
run(1, 2, 6, 6, 0, 1);
run(1, 2, 7, 7, 0, 1);
}
run(1, 1, 3, 2, 1, 1);
run(1, 1, 5, 2, 1, 1);
run(1, 1, 6, 2, 1, 1);
run(1, 1, 7, 2, 1, 1);
run(1, 1, 9, 2, 1, 1);
run(1, 1, 10, 2, 1, 1);
run(1, 1, 11, 2, 1, 1);
run(1, 1, 13, 2, 1, 1);
run(1, 1, 14, 2, 1, 1);
run(1, 1, 15, 2, 1, 1);
run(1, 1, 17, 2, 1, 1);
run(1, 1, 18, 2, 1, 1);
run(1, 1, 19, 2, 1, 1);
run(1, 1, 21, 2, 1, 1);
run(1, 1, 22, 2, 1, 1);
run(1, 1, 23, 2, 1, 1);
run(1, 1, 25, 2, 1, 1);
run(1, 1, 26, 2, 1, 1);
run(1, 1, 27, 2, 1, 1);
run(1, 1, 29, 2, 1, 1);
run(1, 1, 30, 2, 1, 1);
run(1, 1, 31, 2, 1, 1);
run(4, 8, 32, 3, 3 / 2, 1);
run(4, 8, 32, 5, 5 / 2, 1);
run(4, 8, 32, 7, 7 / 2, 1);
run(4, 8, 32, 9, 9 / 2, 1);
run(4, 8, 32, 11, 11 / 2, 1);
......@@ -781,10 +889,24 @@ TEST_F(CUDA, REGION_RESTRICTED_CONV_BWD_DATA_FP32_RIN_EQ_ROUT) {
run(4, 8, 32, 21, 21 / 2, 1);
run(4, 8, 32, 23, 23 / 2, 1);
run(4, 8, 32, 25, 25 / 2, 1);
run(4, 1, 32, 25, 25 / 2, 1);
run(4, 8, 32, 27, 27 / 2, 1);
run(4, 8, 32, 29, 29 / 2, 1);
run(4, 8, 32, 31, 31 / 2, 1);
run(4, 8, 31, 3, 3 / 2, 1);
run(4, 8, 31, 5, 5 / 2, 1);
run(4, 8, 31, 7, 7 / 2, 1);
run(4, 8, 31, 9, 9 / 2, 1);
run(4, 8, 31, 11, 11 / 2, 1);
run(4, 8, 31, 13, 13 / 2, 1);
run(4, 8, 31, 15, 15 / 2, 1);
run(4, 8, 31, 17, 17 / 2, 1);
run(4, 8, 31, 19, 19 / 2, 1);
run(4, 8, 31, 21, 21 / 2, 1);
run(4, 8, 31, 23, 23 / 2, 1);
run(4, 8, 31, 25, 25 / 2, 1);
run(4, 8, 31, 27, 27 / 2, 1);
run(4, 8, 31, 29, 29 / 2, 1);
run(4, 8, 31, 31, 31 / 2, 1);
}
}
......@@ -824,15 +946,13 @@ TEST_F(CUDA, REGION_RESTRICTED_CONV_BWD_FILTER_FP32) {
{g, 1, 1, fh, fh} // grad
});
};
if (dt == dtype::Int32()) {
run(4, 8, 32, 5, 5 / 2, 1);
run(1, 2, 2, 2, 0, 1);
run(1, 2, 3, 3, 0, 1);
run(1, 2, 4, 4, 0, 1);
run(1, 2, 5, 5, 0, 1);
run(1, 2, 6, 6, 0, 1);
run(1, 2, 7, 7, 0, 1);
}
run(4, 8, 32, 5, 5 / 2, 1);
run(1, 2, 2, 2, 0, 1);
run(1, 2, 3, 3, 0, 1);
run(1, 2, 4, 4, 0, 1);
run(1, 2, 5, 5, 0, 1);
run(1, 2, 6, 6, 0, 1);
run(1, 2, 7, 7, 0, 1);
run(4, 8, 32, 7, 7 / 2, 1);
run(4, 8, 32, 9, 9 / 2, 1);
run(4, 8, 32, 11, 11 / 2, 1);
......@@ -886,15 +1006,13 @@ TEST_F(CUDA, REGION_RESTRICTED_CONV_BWD_FILTER_FP32_RIN_EQ_ROUT) {
{g, 1, 1, fh, fh} // grad
});
};
if (dt == dtype::Int32()) {
run(4, 8, 32, 5, 5 / 2, 1);
run(1, 2, 2, 2, 0, 1);
run(1, 2, 3, 3, 0, 1);
run(1, 2, 4, 4, 0, 1);
run(1, 2, 5, 5, 0, 1);
run(1, 2, 6, 6, 0, 1);
run(1, 2, 7, 7, 0, 1);
}
run(4, 8, 32, 5, 5 / 2, 1);
run(1, 2, 2, 2, 0, 1);
run(1, 2, 3, 3, 0, 1);
run(1, 2, 4, 4, 0, 1);
run(1, 2, 5, 5, 0, 1);
run(1, 2, 6, 6, 0, 1);
run(1, 2, 7, 7, 0, 1);
run(4, 8, 32, 7, 7 / 2, 1);
run(4, 8, 32, 9, 9 / 2, 1);
run(4, 8, 32, 11, 11 / 2, 1);
......
imperative/python/test/unit/functional/test_functional.py
浏览文件 @ fa488338
......@@ -1061,8 +1061,8 @@ def test_region_restricted_conv_forward_backward_uint8(bias, groups):
N = 1
GROUP = groups
FH = FW = 1
IH = IW = 4
OH = OW = 4
IH = IW = 3
OH = OW = 3
ICPG = OCPG = 1
grad_shape = (N, GROUP * ICPG, IH, IW)
src_shape = grad_shape
......
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