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This reverts commit c90e00cf85a4ac11e6fd96963e5e95944aefc5b4.
Reverted https://github.com/pytorch/pytorch/pull/82731 on behalf of https://github.com/zengk95 due to This is breaking XLA tests on trunk. It seems to have passed on PR and was able to checkout that commit c90e00cf85
.
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@ -263,10 +263,6 @@ c10::Layout concrete_layout_fn(
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const c10::impl::PyInterpreter*,
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const c10::TensorImpl* self);
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c10::SymInt concrete_sym_numel_fn(
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const c10::impl::PyInterpreter*,
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const c10::TensorImpl* self);
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class PyInterpreterHolder {
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public:
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PyInterpreterHolder()
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@ -281,8 +277,7 @@ class PyInterpreterHolder {
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&concrete_strides_fn,
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&concrete_sizes_fn,
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&concrete_sym_sizes_fn,
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&concrete_layout_fn,
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&concrete_sym_numel_fn)) {}
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&concrete_layout_fn)) {}
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// NB: intentionally leaks the memory
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~PyInterpreterHolder() {
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impl_->disarm();
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@ -2466,31 +2461,4 @@ c10::Layout concrete_layout_fn(
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return toLayout(out.ptr());
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}
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c10::SymInt concrete_sym_numel_fn(
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const c10::impl::PyInterpreter*,
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const c10::TensorImpl* self) {
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pybind11::gil_scoped_acquire gil;
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at::impl::MaybeSetTLSOnEntryGuard guard;
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auto out = torchDispatchFromTensorImpl(
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self,
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"sym_numel",
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py::module::import("torch")
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.attr("ops")
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.attr("aten")
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.attr("sym_numel")
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.attr("default")
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.ptr(),
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"torch.ops.aten");
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if (out == Py_None) {
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TORCH_CHECK(
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!self->has_symbolic_sizes_strides(),
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"Cannot call numel on a tensor with symbolic shapes/strides");
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return self->sym_numel_default();
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}
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return torch::is_symint_node(out)
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? out.cast<c10::SymIntNodeImpl*>()->toSymInt()
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: c10::SymInt{py::cast<int64_t>(out)};
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}
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} // anonymous namespace
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