Merge commit 'be9ef9283f297997afd3bf8e21147ec6bf09ebbf'

Author: soumith

torch/lib/ATen/function_wrapper.py

@@ -391,8 +391,13 @@ def get_arguments(option):
  for argument in option['arguments'] if not drop_argument(argument, option)]
 
  def is_actual_return_long(ret):
- return ret['type'] == 'long' or (backend_type_env['ScalarName'] == 'Long' and
- ret['type'] == 'real' or ret['type'] == 'accreal')
+ if ret['type'] == 'long':
+ return True
+ if ret['type'] == 'real':
+ return backend_type_env['ScalarName'] == 'Long'
+ if ret['type'] == 'accreal':
+ return backend_type_env['AccScalarName'] == 'Long'
+ return False
 
  def handle_zero_dim(env, option):
  if 'zero_dim_dispatch_when_scalar' not in option:

torch/lib/ATen/templates/TensorDerived.cpp

@@ -26,7 +26,11 @@ IntList ${Tensor}::sizes() {
 int64_t ${Tensor}::dim() {
  if(isScalar())
  return 0;
- return ${THTensor}_nDimension(${state,}tensor);
+ int64_t d = ${THTensor}_nDimension(${state,}tensor);
+ if(d != 0)
+ return d;
+ // See Note [Undefined-dim versus 0-dim]
+ return kUndefinedDimensions;
 }
 
 const char * ${Tensor}::typeString() {

torch/lib/ATen/templates/Type.h

@@ -1,6 +1,7 @@
 #pragma once
 
 #include <memory>
+#include <limits>
 
 #include "ATen/ArrayRef.h"
 #include "ATen/Half.h"
@@ -45,6 +46,18 @@ constexpr Backend kCUDA = Backend::CUDA;
 constexpr Backend kSparseCPU = Backend::SparseCPU;
 constexpr Backend kSparseCUDA = Backend::SparseCUDA;
 
+// Note [Undefined-dim versus 0-dim]
+// ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+// Unlike Torch, ATen treats zero-dimension tensors as having ONE
+// element (that is to say, a zero-dimensional tensor is a scalar!)
+// This is in contrast to Torch, where a zero-dimension tensor has
+// zero elements.
+//
+// Because we are backed by Torch tensors, we need to be able to
+// represent this state (of numel==0). kUndefinedDimensions represents this
+// situation.
+constexpr int64_t kUndefinedDimensions = std::numeric_limits<int64_t>::min();
+
 static inline const char * toString(Backend b) {
  switch(b) {
  case Backend::CPU: return "CPU";

torch/lib/ATen/test/basic.cpp

@@ -208,6 +208,9 @@ static void test(Type & type) {
  Tensor b = CPU(kFloat).ones({3,7});
  Tensor c = cat({a,b},1);
  std::cout << c << std::endl;
+
+ Tensor e = CPU(kFloat).rand({});
+ check(*e.data<float>()== e.sum().toFloat());
  }
 
 }