mirror of
https://github.com/wassname/Pointnet2_PyTorch.git
synced 2026-06-27 16:00:07 +08:00
Some updates
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@@ -4,3 +4,6 @@ __pycache__
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runs
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build
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checkpoints
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*.prof
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.lvimrc
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.vimtags
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@@ -88,9 +88,8 @@ class Pointnet2MSG(nn.Module):
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npoint=512,
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radii=[0.1, 0.2, 0.4],
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nsamples=[32, 64, 128],
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mlps=[[input_channels, 32, 32,
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64], [input_channels, 64, 64, 128],
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[input_channels, 64, 96, 128]]
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mlps=[[input_channels, 64], [input_channels, 128],
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[input_channels, 128]]
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)
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)
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@@ -100,9 +99,8 @@ class Pointnet2MSG(nn.Module):
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npoint=128,
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radii=[0.2, 0.4, 0.8],
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nsamples=[16, 32, 64],
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mlps=[[input_channels, 64, 64,
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128], [input_channels, 128, 128, 256],
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[input_channels, 128, 128, 256]]
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mlps=[[input_channels, 128], [input_channels, 256],
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[input_channels, 256]]
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)
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)
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self.SA_modules.append(
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@@ -136,7 +134,6 @@ if __name__ == "__main__":
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model = Pointnet2MSG(3)
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model.cuda()
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optimizer = optim.Adam(model.parameters(), lr=1e-2)
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model_fn = model_fn_decorator(nn.CrossEntropyLoss())
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@@ -1,24 +1,12 @@
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#ifndef _CUDA_UTILS_H
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#define _CUDA_UTILS_H
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#ifdef __cplusplus
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extern "C" {
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#endif
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#include <cmath>
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inline int opt_n_threads(int work_size) {
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unsigned int n_threads = work_size;
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n_threads--;
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n_threads |= n_threads >> 1;
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n_threads |= n_threads >> 2;
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n_threads |= n_threads >> 4;
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n_threads |= n_threads >> 8;
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n_threads |= n_threads >> 16;
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n_threads++;
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const int pow_2 = std::log(static_cast<double>(work_size)) / std::log(2.0);
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return max(min(n_threads / 2, 512), 2);
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return max(min(1 << pow_2, 512), 32);
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}
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#ifdef __cplusplus
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}
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#endif
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#endif
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@@ -13,9 +13,10 @@ __global__ void gather_points_kernel(int b, int n, int c, int m,
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for (int i = blockIdx.x; i < b; i += gridDim.x) {
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for (int j = blockIdx.y * blockDim.x + threadIdx.x; j < m;
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j += blockDim.x * gridDim.y) {
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int a = idx[i * m + j];
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memcpy(out + (i * m + j) * c, points + (i * n + a) * c,
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sizeof(float) * c);
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const int jj = idx[i * m + j];
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for (int l = 0; l < c; ++l) {
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out[(i * m + j) * c + l] = points[(i * n + jj) * c + l];
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}
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}
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}
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}
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@@ -25,7 +26,7 @@ void gather_points_kernel_wrapper(int b, int n, int c, int npoints,
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float *out, cudaStream_t stream) {
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cudaError_t err;
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gather_points_kernel<<<dim3(2, 8, 1), opt_n_threads(npoints) / 4, 0,
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gather_points_kernel<<<dim3(b, 8, 1), opt_n_threads(npoints), 0,
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stream>>>(b, n, c, npoints, points, idx, out);
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err = cudaGetLastError();
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