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torch C API warnings

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Summary: This is mostly replacing the old PackedTensorAccessor with the new PackedTensorAccessor64.

Reviewed By: gkioxari

Differential Revision: D21088773

fbshipit-source-id: 5973e5a29d934eafb7c70ec5ec154ca076b64d27
This commit is contained in:
Jeremy Reizenstein
2020-04-17 10:37:10 -07:00
committed by Facebook GitHub Bot
parent f25af96959
commit 9397cd872d
6 changed files with 60 additions and 63 deletions
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40
pytorch3d/csrc/compositing/alpha_composite.cu
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@@ -12,10 +12,10 @@
// Currently, support is for floats only.
__global__ void alphaCompositeCudaForwardKernel(
// clang-format off
torch::PackedTensorAccessor<float, 4, torch::RestrictPtrTraits, size_t> result,
const torch::PackedTensorAccessor<float, 2, torch::RestrictPtrTraits, size_t> features,
const torch::PackedTensorAccessor<float, 4, torch::RestrictPtrTraits, size_t> alphas,
const torch::PackedTensorAccessor<int64_t, 4, torch::RestrictPtrTraits, size_t> points_idx) {
torch::PackedTensorAccessor64<float, 4, torch::RestrictPtrTraits> result,
const torch::PackedTensorAccessor64<float, 2, torch::RestrictPtrTraits> features,
const torch::PackedTensorAccessor64<float, 4, torch::RestrictPtrTraits> alphas,
const torch::PackedTensorAccessor64<int64_t, 4, torch::RestrictPtrTraits> points_idx) {
// clang-format on
const int64_t batch_size = result.size(0);
const int64_t C = features.size(0);
@@ -61,12 +61,12 @@ __global__ void alphaCompositeCudaForwardKernel(
// Currently, support is for floats only.
__global__ void alphaCompositeCudaBackwardKernel(
// clang-format off
torch::PackedTensorAccessor<float, 2, torch::RestrictPtrTraits, size_t> grad_features,
torch::PackedTensorAccessor<float, 4, torch::RestrictPtrTraits, size_t> grad_alphas,
const torch::PackedTensorAccessor<float, 4, torch::RestrictPtrTraits, size_t> grad_outputs,
const torch::PackedTensorAccessor<float, 2, torch::RestrictPtrTraits, size_t> features,
const torch::PackedTensorAccessor<float, 4, torch::RestrictPtrTraits, size_t> alphas,
const torch::PackedTensorAccessor<int64_t, 4, torch::RestrictPtrTraits, size_t> points_idx) {
torch::PackedTensorAccessor64<float, 2, torch::RestrictPtrTraits> grad_features,
torch::PackedTensorAccessor64<float, 4, torch::RestrictPtrTraits> grad_alphas,
const torch::PackedTensorAccessor64<float, 4, torch::RestrictPtrTraits> grad_outputs,
const torch::PackedTensorAccessor64<float, 2, torch::RestrictPtrTraits> features,
const torch::PackedTensorAccessor64<float, 4, torch::RestrictPtrTraits> alphas,
const torch::PackedTensorAccessor64<int64_t, 4, torch::RestrictPtrTraits> points_idx) {
// clang-format on
const int64_t batch_size = points_idx.size(0);
const int64_t C = features.size(0);
@@ -149,10 +149,10 @@ torch::Tensor alphaCompositeCudaForward(
// doubles. Currently, support is for floats only.
alphaCompositeCudaForwardKernel<<<numBlocks, threadsPerBlock>>>(
// clang-format off
result.packed_accessor<float, 4, torch::RestrictPtrTraits, size_t>(),
features.packed_accessor<float, 2, torch::RestrictPtrTraits, size_t>(),
alphas.packed_accessor<float, 4, torch::RestrictPtrTraits, size_t>(),
points_idx.packed_accessor<int64_t, 4, torch::RestrictPtrTraits, size_t>());
result.packed_accessor64<float, 4, torch::RestrictPtrTraits>(),
features.packed_accessor64<float, 2, torch::RestrictPtrTraits>(),
alphas.packed_accessor64<float, 4, torch::RestrictPtrTraits>(),
points_idx.packed_accessor64<int64_t, 4, torch::RestrictPtrTraits>());
// clang-format on
return result;
@@ -175,12 +175,12 @@ std::tuple<torch::Tensor, torch::Tensor> alphaCompositeCudaBackward(
// doubles. Currently, support is for floats only.
alphaCompositeCudaBackwardKernel<<<numBlocks, threadsPerBlock>>>(
// clang-format off
grad_features.packed_accessor<float, 2, torch::RestrictPtrTraits, size_t>(),
grad_alphas.packed_accessor<float, 4, torch::RestrictPtrTraits, size_t>(),
grad_outputs.packed_accessor<float, 4, torch::RestrictPtrTraits, size_t>(),
features.packed_accessor<float, 2, torch::RestrictPtrTraits, size_t>(),
alphas.packed_accessor<float, 4, torch::RestrictPtrTraits, size_t>(),
points_idx.packed_accessor<int64_t, 4, torch::RestrictPtrTraits, size_t>());
grad_features.packed_accessor64<float, 2, torch::RestrictPtrTraits>(),
grad_alphas.packed_accessor64<float, 4, torch::RestrictPtrTraits>(),
grad_outputs.packed_accessor64<float, 4, torch::RestrictPtrTraits>(),
features.packed_accessor64<float, 2, torch::RestrictPtrTraits>(),
alphas.packed_accessor64<float, 4, torch::RestrictPtrTraits>(),
points_idx.packed_accessor64<int64_t, 4, torch::RestrictPtrTraits>());
// clang-format on
return std::make_tuple(grad_features, grad_alphas);