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Call PyArray_Check only if NumPy is available #66433

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2 changes: 2 additions & 0 deletions .jenkins/pytorch/test.sh
Expand Up @@ -222,6 +222,8 @@ 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
}

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2 changes: 1 addition & 1 deletion torch/csrc/utils/tensor_new.cpp
Expand Up @@ -201,7 +201,7 @@ 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 "
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