Make NumPy dependency dynamic (#52794)

Summary:
Move NumPy initialization from `initModule()` to singleton inside
`torch::utils::is_numpy_available()` function.
This singleton will print a warning, that NumPy integration is not
available, rather than fails to import torch altogether.
The warning be printed only once, and will look something like the
following:
```
UserWarning: Failed to initialize NumPy: No module named 'numpy.core' (Triggered internally at  ../torch/csrc/utils/tensor_numpy.cpp:66.)
```

This is helpful if PyTorch was compiled with wrong NumPy version, of
NumPy is not commonly available on the platform (which is often the case
on AARCH64 or Apple M1)

Test that PyTorch is usable after numpy is uninstalled at the end of
`_test1` CI config.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/52794

Reviewed By: seemethere

Differential Revision: D26650509

Pulled By: malfet

fbshipit-source-id: a2d98769ef873862c3704be4afda075d76d3ad06

torch/csrc/Module.cpp

@@ -71,9 +71,6 @@
 #include <callgrind.h>
 #endif
 
-#define WITH_NUMPY_IMPORT_ARRAY
-#include <torch/csrc/utils/numpy_stub.h>
-
 namespace py = pybind11;
 
 PyObject* module;
@@ -1004,9 +1001,6 @@ Call this whenever a new thread is created in order to propagate values from
   ASSERT_TRUE(set_module_attr("DisableTorchFunction", (PyObject*)THPModule_DisableTorchFunctionType(), /* incref= */ false));
   torch::set_disabled_torch_function_impl(PyObject_GetAttrString(module, "_disabled_torch_function_impl"));
   ASSERT_TRUE(torch::disabled_torch_function_impl() != nullptr);
-#ifdef USE_NUMPY
-  if (_import_array() < 0) return nullptr;
-#endif
   return module;
   END_HANDLE_TH_ERRORS
 }