Remove BUILD_NAMEDTENSOR macros (#30894)

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/30894

This PR begins the process of removing BUILD_NAMEDTENSOR macros. There
will be followups.

Reasons for removing the macros:
- BUILD_NAMEDTENSOR is always on and has been on since pytorch 1.3.0.
- Since we don't test building without it, it is useless to keep around.
- Code becomes nicer to read without the macros

Reasons for not removing the macros:
- potential for feature flagging

Now, I argue against needing to feature flag. The main reason why we
might want to feature flag is if we need to disable the feature.
We'd need a fast switch to disable the feature if someone discovers
in the future that named tensors caused some regression in some existing workflows.

In https://github.com/pytorch/pytorch/pull/25798, I did a variety of
macro- and micro- benchmarks to determine the performance impact of named
tensors on regular tensors.

[The
microbenchmarks](https://github.com/pytorch/pytorch/pull/25798#issuecomment-529014810)
were not very stable, and running the
microbenchmarks for more iterations doesn't actually help because the
noise is not distributed in a nice way. Instead of microbenchmarks I ran
a [profiler
(perf)](https://github.com/pytorch/pytorch/pull/25798#issuecomment-555707645)
to estimate how much overhead named tensors add to unnamed code. I
estimated the overhead to be less than 100ns for `add` and even smaller
for `mm`; there are ways to optimize even futher if we find this to be a
problem.

[Initial
macrobenchmarks](https://github.com/pytorch/pytorch/pull/25798#issuecomment-530539104)
were also not very stable. I ran imagenet for some number of epochs. To
make them more stable, I got rid of the data loading (which seemed to
vary between runs). [In some benchmarkers without data
loading](https://github.com/pytorch/pytorch/pull/25798#issuecomment-562214053),
we can see that the results are less noisy now. These results support
no noticeable regressions in speed.

Test Plan: - wait for CI

Differential Revision: D18858543

Pulled By: zou3519

fbshipit-source-id: 08bf3853a9f506c6b084808dc9ddd1e835f48c13

torch/csrc/autograd/python_variable.cpp

@@ -25,9 +25,7 @@
 #include <torch/csrc/utils/tensor_new.h>
 #include <torch/csrc/jit/tracer.h>
 #include <ATen/core/EnableNamedTensor.h>
-#ifdef BUILD_NAMEDTENSOR
 #include <ATen/NamedTensorUtils.h>
-#endif
 
 #include <ATen/ATen.h>
 #include <pybind11/pybind11.h>
@@ -323,7 +321,6 @@ PyObject *THPVariable_get_ndim(THPVariable *self, void *unused)
   END_HANDLE_TH_ERRORS
 }
 
-#ifdef BUILD_NAMEDTENSOR
 PyObject *THPVariable_get_names(THPVariable *self, void *unused)
 {
   HANDLE_TH_ERRORS
@@ -370,7 +367,6 @@ int THPVariable_set_names(THPVariable *self, PyObject *names) {
   return 0;
   END_HANDLE_TH_ERRORS_RET(-1)
 }
-#endif
 
 int THPVariable_set_requires_grad(THPVariable *self, PyObject *obj, void *unused)
 {
@@ -524,9 +520,7 @@ static struct PyGetSetDef THPVariable_properties[] = {
   {"layout", (getter)THPVariable_layout, nullptr, nullptr, nullptr},
   {"device", (getter)THPVariable_device, nullptr, nullptr, nullptr},
   {"ndim", (getter)THPVariable_get_ndim, nullptr, nullptr, nullptr},
-#ifdef BUILD_NAMEDTENSOR
   {"names", (getter)THPVariable_get_names, (setter)THPVariable_set_names, nullptr, nullptr},
-#endif
   {nullptr}
 };