Renaming dims() to sizes() (caffe2/caffe2) - 3/4 (pytorch#13096)

Summary:
Pull Request resolved: pytorch#13096

Codemod generated with clangr shard mode, 25 files per diff, for renaming dims() to sizes()

Reviewed By: ezyang

Differential Revision: D10842875

fbshipit-source-id: 1784859735ed4d1bd5ccd7ca56e289498374a68f

Author: jerryzh168

caffe2/ideep/operators/concat_split_op.cc

@@ -37,9 +37,9 @@ class IDEEPConcatOp final : public IDEEPOperator {
             BlobIsTensorType(OperatorBase::InputBlob(i), CPU),
             "Expect cpu tensor if not itensor");
         auto& tensor_cpu = OperatorBase::Input<Tensor>(i, CPU);
-        CAFFE_ENFORCE(tensor_cpu.dims().size() == 0 ||
-                      tensor_cpu.numel() == 0,
-                      "Expect zero dim tensor");
+        CAFFE_ENFORCE(
+            tensor_cpu.sizes().size() == 0 || tensor_cpu.numel() == 0,
+            "Expect zero dim tensor");
       }
     }
 

caffe2/ideep/operators/utility_ops.cc

@@ -12,7 +12,7 @@ class CopyCPUToIDEEPOp final : public IDEEPOperator {
   bool RunOnDevice() override {
     const auto& X = OperatorBase::Input<Tensor>(0, CPU);
     auto* Y = OperatorBase::OutputBlob(0);
-    itensor::dims src_dims(X.dims().begin(), X.dims().end());
+    itensor::dims src_dims(X.sizes().begin(), X.sizes().end());
     if (!(Y->template IsType<itensor>() &&
           Y->Get<itensor>().get_data_type() == itensor::data_type::f32) ||
         Y->Get<itensor>().get_dims() != src_dims) {

caffe2/mpi/mpi_ops.h

@@ -98,7 +98,7 @@ class MPIAllgatherOp final : public Operator<Context> {
     MPI_Comm comm = OperatorBase::Input<MPICommonWorldWrapper>(0).comm();
     auto& input = Input(1);
     auto* output = Output(0);
-    vector<int64_t> output_dims = input.dims().vec();
+    vector<int64_t> output_dims = input.sizes().vec();
     output_dims[0] *= OperatorBase::Input<MPICommonWorldWrapper>(0).size();
     output->Resize(output_dims);
     MPI_CHECK(MPI_Allgather(

caffe2/predictor/predictor.cc

@@ -34,7 +34,7 @@ void exportOutputTensor(
     const std::string& name,
     TensorCPU& output) {
   auto tensor = getTensor(ws, name);
-  output.Resize(tensor->dims());
+  output.Resize(tensor->sizes());
   output.ShareData(*tensor);
 }
 

caffe2/predictor/predictor_test.cc

@@ -186,7 +186,7 @@ TEST_F(PredictorTest, SimpleBatchSized) {
   Predictor::TensorList output;
   (*p_)(input, &output);
   EXPECT_EQ(output.size(), 1);
-  EXPECT_EQ(output.front().dims().size(), 2);
+  EXPECT_EQ(output.front().sizes().size(), 2);
   EXPECT_EQ(output.front().dim(0), 1);
   EXPECT_EQ(output.front().dim(1), 10);
   EXPECT_NEAR(output.front().data<float>()[4], 0.1209, 1E-4);
@@ -203,7 +203,7 @@ TEST_F(PredictorTest, SimpleBatchSizedMapInput) {
   Predictor::TensorList output;
   (*p_)(input, &output);
   EXPECT_EQ(output.size(), 1);
-  EXPECT_EQ(output.front().dims().size(), 2);
+  EXPECT_EQ(output.front().sizes().size(), 2);
   EXPECT_EQ(output.front().dim(0), 1);
   EXPECT_EQ(output.front().dim(1), 10);
   EXPECT_NEAR(output.front().data<float>()[4], 0.1209, 1E-4);

caffe2/python/pybind_state.cc

@@ -402,7 +402,7 @@ void addObjectMethods(py::module& m) {
             // be, since we're doing an extra allocation we didn't
             // need to do.  But I don't remember how to clue in
             // pybind11 how to convert ArrayRef to vector.
-            return tensor->dims().vec();
+            return tensor->sizes().vec();
           })
       .def(
           "_reshape",