Rename IntList to IntArrayRef. (#16751)

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/16751

This was made more complicated by the fact that ivalue::IntList
is a thing.  So I had to fix all of the sites where we referring
to IValue post facto.

The following codemods were run, in this order:

```
codemod -m -d . --extensions cc,cpp,cu,cuh,h,hpp,py,cwrap,yaml,in IntList IntArrayRef
codemod -m -d . --extensions cc,cpp,cu,cuh,h,hpp,py,cwrap,yaml,in IntArrayRef::create IntList::create
codemod -m -d . --extensions cc,cpp,cu,cuh,h,hpp,py,cwrap,yaml,in ivalue::IntArrayRef ivalue::IntList
codemod -m -d . --extensions cc,cpp,cu,cuh,h,hpp,py,cwrap,yaml,in Tag::IntArrayRef Tag::IntList
codemod -m -d . --extensions cc,cpp,cu,cuh,h,hpp,py,cwrap,yaml,in isIntArrayRef isIntList
codemod -m -d . --extensions cc,cpp,cu,cuh,h,hpp,py,cwrap,yaml,in toIntArrayRef toIntList
codemod -m -d . --extensions cc,cpp,cu,cuh,h,hpp,py,cwrap,yaml,in 'Shared<IntArrayRef>' 'Shared<IntList>'
codemod -m -d . --extensions cc,cpp,cu,cuh,h,hpp,py,cwrap,yaml,in 'intrusive_ptr<IntArrayRef>' 'intrusive_ptr<IntList>'
```

Some manual fixups were done afterwards; they can be reviewed separately
at https://github.com/pytorch/pytorch/pull/16752

Reviewed By: dzhulgakov

Differential Revision: D13954363

fbshipit-source-id: b5c40aacba042402155a2f5a229fa6db7992ac64

4 files changed, 16 insertions, 16 deletions

diff --git a/caffe2/core/blob.h b/caffe2/core/blob.h
index 4613aee6a5..f919a7ac16 100644
--- a/caffe2/core/blob.h
+++ b/caffe2/core/blob.h
@@ -30,7 +30,7 @@ inline Tensor* BlobSetTensor(Blob* blob, Tensor&& tensor) {
 
 inline Tensor GetSizedTensorWithOptions(
     Tensor&& previous_tensor,
-    at::IntList dims,
+    at::IntArrayRef dims,
     at::TensorOptions options) {
   Tensor tensor = std::move(previous_tensor);
   if (!tensor.defined()) {
@@ -57,7 +57,7 @@ inline Tensor GetSizedTensorWithOptions(
 // need to keep both functions that returns Tensor* and the one
 // returns Tensor for clangr codemod
 inline Tensor*
-BlobGetMutableTensor(Blob* blob, at::IntList dims, at::TensorOptions options) {
+BlobGetMutableTensor(Blob* blob, at::IntArrayRef dims, at::TensorOptions options) {
   if (blob->IsType<Tensor>()) {
     Tensor* tensor = blob->GetMutable<Tensor>();
     if (*tensor) {
@@ -86,7 +86,7 @@ BlobGetMutableTensor(Blob* blob, at::IntList dims, at::TensorOptions options) {
 }
 
 inline Tensor
-XBlobGetMutableTensor(Blob* blob, at::IntList dims, at::TensorOptions options) {
+XBlobGetMutableTensor(Blob* blob, at::IntArrayRef dims, at::TensorOptions options) {
   return BlobGetMutableTensor(blob, dims, options)->UnsafeSharedInstance();
 }
 
diff --git a/caffe2/core/operator.h b/caffe2/core/operator.h
index 423a1b73f2..eea3a58d29 100644
--- a/caffe2/core/operator.h
+++ b/caffe2/core/operator.h
@@ -196,7 +196,7 @@ class CAFFE2_API OperatorBase : public Observable<OperatorBase> {
   }
 
   inline Tensor
-  XOutputTensor(int idx, at::IntList dims, at::TensorOptions options) {
+  XOutputTensor(int idx, at::IntArrayRef dims, at::TensorOptions options) {
     CAFFE_ENFORCE_WITH_CALLER(
         options.device_opt() != c10::nullopt,
         "device must be provided in option.");
@@ -214,7 +214,7 @@ class CAFFE2_API OperatorBase : public Observable<OperatorBase> {
   }
 
   inline Tensor*
-  OutputTensor(int idx, at::IntList dims, at::TensorOptions options) {
+  OutputTensor(int idx, at::IntArrayRef dims, at::TensorOptions options) {
     if (isLegacyOperator()) {
       CAFFE_ENFORCE_WITH_CALLER(
           options.device_opt() != c10::nullopt,
@@ -667,7 +667,7 @@ class Operator : public OperatorBase {
     return OperatorBase::template Input<Tensor>(idx, type);
   }
 
-  Tensor XOutput(int idx, at::IntList dims, at::TensorOptions options) {
+  Tensor XOutput(int idx, at::IntArrayRef dims, at::TensorOptions options) {
     // We'll default device to the device of the current Operator Context
     if (options.device_opt() == c10::nullopt) {
       return OperatorBase::XOutputTensor(
@@ -724,7 +724,7 @@ class Operator : public OperatorBase {
   /// helpful, as we may be able to fit the output in the same
   /// space that was previously used.
   ///
-  Tensor* Output(int idx, at::IntList dims, at::TensorOptions options) {
+  Tensor* Output(int idx, at::IntArrayRef dims, at::TensorOptions options) {
     // We'll default device to the device of the current Operator Context
     if (options.device_opt() == c10::nullopt) {
       return OperatorBase::OutputTensor(
diff --git a/caffe2/core/tensor.cc b/caffe2/core/tensor.cc
index 8bd5190710..afcae812be 100644
--- a/caffe2/core/tensor.cc
+++ b/caffe2/core/tensor.cc
@@ -117,7 +117,7 @@ void TensorVectorResize(
   }
 }
 
-Tensor empty(at::IntList dims, at::TensorOptions options) {
+Tensor empty(at::IntArrayRef dims, at::TensorOptions options) {
   // TODO: merge this with at::empty after Tensor is merged
   auto tensor = Tensor(dims, options.device());
   tensor.raw_mutable_data(options.dtype());
@@ -126,7 +126,7 @@ Tensor empty(at::IntList dims, at::TensorOptions options) {
 
 void ReinitializeTensor(
     Tensor* tensor,
-    at::IntList dims,
+    at::IntArrayRef dims,
     at::TensorOptions options) {
   CAFFE_ENFORCE(options.device_opt() != c10::nullopt);
   if (*tensor) {
diff --git a/caffe2/core/tensor.h b/caffe2/core/tensor.h
index 5e042a5977..f86f93c053 100644
--- a/caffe2/core/tensor.h
+++ b/caffe2/core/tensor.h
@@ -83,7 +83,7 @@ class CAFFE2_API Tensor final {
    * Note that the actual data allocation is not going to be carried out until
    * the first time mutable_data() is called.
    */
-  explicit Tensor(at::IntList dims, DeviceType type) : Tensor(type) {
+  explicit Tensor(at::IntArrayRef dims, DeviceType type) : Tensor(type) {
     // TODO: here, we create a Storage
     // and immediately discard it in Resize() since
     // reset_tensor will be true and FreeMemory will be called,
@@ -92,7 +92,7 @@ class CAFFE2_API Tensor final {
   }
 
   // we want to preserve index information
-  explicit Tensor(at::IntList dims, at::Device device): Tensor(device) {
+  explicit Tensor(at::IntArrayRef dims, at::Device device): Tensor(device) {
     Resize(dims);
   }
 
@@ -500,7 +500,7 @@ class CAFFE2_API Tensor final {
     return impl_->numel() * itemsize();
   }
 
-  inline at::IntList sizes() const {
+  inline at::IntArrayRef sizes() const {
     return impl_.get()->sizes();
   }
 
@@ -535,7 +535,7 @@ class CAFFE2_API Tensor final {
     return impl_.get()->stride(dim);
   }
 
-  inline at::IntList strides() const {
+  inline at::IntArrayRef strides() const {
     return impl_.get()->strides();
   }
 
@@ -614,7 +614,7 @@ class CAFFE2_API Tensor final {
  * this will not do anything if the
  * Tensor already has correct size and data type
  */
-CAFFE2_API void ReinitializeTensor(Tensor* t, at::IntList dims, at::TensorOptions options);
+CAFFE2_API void ReinitializeTensor(Tensor* t, at::IntArrayRef dims, at::TensorOptions options);
 
 CAFFE2_API void ReinitializeAndCopyFrom(
     Tensor* t,
@@ -651,7 +651,7 @@ void TensorVectorResize(
     DeviceType type);
 
 // Tensor factory function
-CAFFE2_API Tensor empty(at::IntList dims, at::TensorOptions options);
+CAFFE2_API Tensor empty(at::IntArrayRef dims, at::TensorOptions options);
 
 /**
  * @brief Creates a CPU tensor, and fills its contents with the given values.
@@ -660,7 +660,7 @@ CAFFE2_API Tensor empty(at::IntList dims, at::TensorOptions options);
 // TODO: can be unified with at::from_blob when Tensor is merged and string
 // types are supported
 template <typename T>
-Tensor TensorCPUFromValues(at::IntList dims, at::ArrayRef<T> values) {
+Tensor TensorCPUFromValues(at::IntArrayRef dims, at::ArrayRef<T> values) {
   Tensor r = empty(dims, at::device(CPU).dtype<T>());
   CAFFE_ENFORCE_EQ(values.size(), r.numel());
   CPUContext context;