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https://github.com/zebrajr/pytorch.git
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f884e817d4
See strategy at PythonOpRegistrationTrampoline.cpp for the big picture. Along the way, I made OperatorHandle support == and hashing, and slightly changed the low level python_dispatch impl API to disallow empty strings for dispatch key, which had the knock on effect of requiring us to explicitly make sure we pass in CompositeImplicitAutograd if we would have passed in "" (I didn't apply this to the rest of the file because I'm lazy.) Test strategy is we delete the logic for preventing Python op registrations in torch from being skipped in a torchdeploy context and show CI still works. Signed-off-by: Edward Z. Yang <ezyang@fb.com> Pull Request resolved: https://github.com/pytorch/pytorch/pull/87162 Approved by: https://github.com/anjali411, https://github.com/bdhirsh
104 lines
3.3 KiB
C++
104 lines
3.3 KiB
C++
#include <c10/core/SymIntArrayRef.h>
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#include <c10/core/TensorImpl.h>
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#include <c10/core/impl/PyInterpreter.h>
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namespace c10 {
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namespace impl {
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struct NoopPyInterpreterVTable final : public PyInterpreterVTable {
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std::string name() const override {
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return "<unloaded interpreter>";
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}
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void decref(PyObject* pyobj, bool is_tensor) const override {} // do nothing
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#define PANIC(m) \
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TORCH_INTERNAL_ASSERT( \
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0, \
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"attempted to call " #m \
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" on a Tensor with nontrivial PyObject after corresponding interpreter died")
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c10::intrusive_ptr<TensorImpl> detach(const TensorImpl* self) const override {
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PANIC(detach);
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}
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void dispatch(const c10::OperatorHandle& op, torch::jit::Stack* stack)
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const override {
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PANIC(dispatch);
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}
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void python_op_registration_trampoline(
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const c10::OperatorHandle& op,
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c10::DispatchKey,
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torch::jit::Stack* stack) const override {
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PANIC(python_op_registration_trampoline);
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}
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void python_dispatcher(
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const c10::OperatorHandle& op,
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c10::DispatchKeySet,
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torch::jit::Stack* stack) const override {
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PANIC(python_dispatcher);
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}
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bool is_contiguous(const TensorImpl* self, at::MemoryFormat) const override {
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PANIC(is_contiguous);
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}
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bool is_strides_like(const TensorImpl* self, at::MemoryFormat)
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const override {
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PANIC(is_strides_like);
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}
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bool is_non_overlapping_and_dense(const TensorImpl* self) const override {
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PANIC(is_non_overlapping_and_dense);
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}
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c10::Device device(const TensorImpl* self) const override {
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PANIC(device);
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}
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int64_t dim(const TensorImpl* self) const override {
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PANIC(dim);
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}
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c10::IntArrayRef strides(const TensorImpl* self) const override {
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PANIC(strides);
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}
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c10::IntArrayRef sizes(const TensorImpl* self) const override {
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PANIC(sizes);
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}
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c10::SymIntArrayRef sym_sizes(const TensorImpl* self) const override {
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PANIC(sym_sizes);
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}
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c10::Layout layout(const TensorImpl* self) const override {
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PANIC(layout);
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}
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c10::SymInt sym_numel(const TensorImpl* self) const override {
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PANIC(sym_numel);
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}
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c10::SymIntArrayRef sym_strides(const TensorImpl* self) const override {
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PANIC(sym_strides);
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}
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c10::SymInt sym_storage_offset(const TensorImpl* self) const override {
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PANIC(sym_storage_offset);
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}
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// Just swallow the event, don't do anything
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void trace_gpu_event_creation(uintptr_t event) const override {}
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void trace_gpu_event_deletion(uintptr_t event) const override {}
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void trace_gpu_event_record(uintptr_t event, uintptr_t stream)
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const override {}
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void trace_gpu_event_wait(uintptr_t event, uintptr_t stream) const override {}
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void trace_gpu_memory_allocation(uintptr_t ptr) const override {}
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void trace_gpu_memory_deallocation(uintptr_t ptr) const override {}
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void trace_gpu_stream_creation(uintptr_t stream) const override {}
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void trace_gpu_device_synchronization() const override {}
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void trace_gpu_stream_synchronization(uintptr_t stream) const override {}
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void trace_gpu_event_synchronization(uintptr_t event) const override {}
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};
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void PyInterpreter::disarm() noexcept {
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// Intentionally leaked
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static PyInterpreterVTable* noop_vtable = new NoopPyInterpreterVTable();
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vtable_ = noop_vtable;
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}
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} // namespace impl
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} // namespace c10
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