Call PyArray_Check only if NumPy is available (#66433) (#66629)

Summary:
Fixes #66353

Fixes #{issue number}

Pull Request resolved: #66433

Reviewed By: seemethere, janeyx99

Differential Revision: D31548290

Pulled By: malfet

fbshipit-source-id: 3b094bc8195d0392338e0bdc6df2f39587b85bb3

.jenkins/pytorch/test.sh

@@ -230,6 +230,8 @@ test_aten() {
 test_without_numpy() {
   pushd "$(dirname "${BASH_SOURCE[0]}")"
   python -c "import sys;sys.path.insert(0, 'fake_numpy');from unittest import TestCase;import torch;x=torch.randn(3,3);TestCase().assertRaises(RuntimeError, lambda: x.numpy())"
+  # Regression test for https://github.com/pytorch/pytorch/issues/66353
+  python -c "import sys;sys.path.insert(0, 'fake_numpy');import torch;print(torch.tensor([torch.tensor(0.), torch.tensor(1.)]))"
   popd
 }
 

torch/csrc/utils/tensor_new.cpp

@@ -194,7 +194,7 @@ void recursive_store(char* data, IntArrayRef sizes, IntArrayRef strides, int64_t
   PyObject** items = PySequence_Fast_ITEMS(seq.get());
   for(const auto i : c10::irange(n)) {
 #ifdef USE_NUMPY
-    if (PyArray_Check(items[i])) {
+    if (is_numpy_available() && PyArray_Check(items[i])) {
       TORCH_WARN_ONCE(
         "Creating a tensor from a list of numpy.ndarrays is extremely slow. "
         "Please consider converting the list to a single numpy.ndarray with "