dims() to sizes() remaining part

Summary: Made the clangr rule more robust and it discovered more callsites.

Reviewed By: smessmer

Differential Revision: D12825017

fbshipit-source-id: 3be1eeb7ea697b36ef89e78ba64c0ee1259439c4

Author: jerryzh168

caffe2/contrib/nccl/cuda_nccl_gpu.cc

@@ -205,7 +205,7 @@ void NCCL<T>::AllReduce(const NCCLExecution& ex) {
   return runNCCL<T>(
       ex,
       [](const NCCLElement& ctx) {
-        ctx.dst->Resize(ctx.src->dims());
+        ctx.dst->Resize(ctx.src->sizes());
         ctx.dst->template mutable_data<T>();
       },
       [](const NCCLElement& ctx, ncclComm_t comm, cudaStream_t stream) {
@@ -225,7 +225,7 @@ void NCCL<T>::Broadcast(const NCCLExecution& ex) {
   return runNCCL<T>(
       ex,
       [](const NCCLElement& ctx) {
-        ctx.dst->Resize(ctx.src->dims());
+        ctx.dst->Resize(ctx.src->sizes());
         ctx.dst->template mutable_data<T>();
       },
       [&ex](const NCCLElement& ctx, ncclComm_t comm, cudaStream_t stream) {
@@ -245,7 +245,7 @@ void NCCL<T>::Reduce(const NCCLExecution& ex) {
       ex,
       [](const NCCLElement& ctx) {
         if (ctx.dst) {
-          ctx.dst->Resize(ctx.src->dims());
+          ctx.dst->Resize(ctx.src->sizes());
           ctx.dst->template mutable_data<T>();
         }
       },
@@ -272,7 +272,7 @@ void NCCL<T>::AllGather(const NCCLExecution& ex) {
         std::vector<int64_t> dims;
         dims.reserve(ctx.src->ndim() + 1);
         dims.push_back(n);
-        for (auto d : ctx.src->dims()) {
+        for (auto d : ctx.src->sizes()) {
           dims.push_back(d);
         }
         ctx.dst->Resize(dims);
@@ -306,7 +306,7 @@ void NCCL<T>::ReduceScatter(const NCCLExecution& ex) {
       ex,
       [](const NCCLElement& ctx) {
         CAFFE_ENFORCE_NE(ctx.src, ctx.dst);
-        const auto& srcDims = ctx.src->dims();
+        const auto& srcDims = ctx.src->sizes();
         std::vector<int64_t> dstDims(srcDims.begin() + 1, srcDims.end());
         ctx.dst->Resize(dstDims);
         ctx.dst->template mutable_data<T>();

caffe2/operators/dataset_ops.cc

@@ -156,7 +156,7 @@ void TreeWalker::advance() {
 }
 
 std::vector<int64_t> TreeWalker::fieldDim(int fieldId) const {
-  auto tensorDim = input(fieldId).dims().vec();
+  auto tensorDim = input(fieldId).sizes().vec();
   tensorDim[0] = sizes_[lengthIdx(fieldId)];
   return tensorDim;
 }
@@ -185,7 +185,7 @@ void TreeWalker::gatherSizeLimits() {
   for (auto fieldId = 0; fieldId < cursor_.it.fields().size(); ++fieldId) {
     auto lengthFieldIdx = lengthIdx(fieldId);
     limits_[lengthFieldIdx] =
-        std::min(limits_[lengthFieldIdx], (TOffset)input(fieldId).dims()[0]);
+        std::min(limits_[lengthFieldIdx], (TOffset)input(fieldId).sizes()[0]);
   }
 }
 

caffe2/operators/generate_proposals_op.cc

@@ -37,7 +37,7 @@ utils::ConstTensorView<T> GetSubTensorView(
   auto st_idx = ComputeStartIndex(tensor, start_dims);
   auto ptr = tensor.data<T>() + st_idx;
 
-  auto input_dims = tensor.dims();
+  auto input_dims = tensor.sizes();
   std::vector<int> ret_dims(input_dims.begin() + 1, input_dims.end());
 
   utils::ConstTensorView<T> ret(ptr, ret_dims);

caffe2/python/pybind_state.cc

@@ -460,7 +460,7 @@ void addObjectMethods(py::module& m) {
           "Initialize this tensor to given shape and data type. "
           "Fail if the given data type cannot be accessed from python.")
       .def_property_readonly(
-          "_shape", [](const TensorCPU& t) { return t.dims().vec(); })
+          "_shape", [](const TensorCPU& t) { return t.sizes().vec(); })
       .def("_reshape", [](TensorCPU* t, std::vector<int64_t> dims) {
         t->Resize(dims);
       });