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ed49792a0c
Run DeepInfer on the native torch-neuronx device (PrivateUse1 `neuron`, torch-neuronx 2.14, no torch-xla), following the Ascend port's structure. - deep_cluster: Neuron discovery (one DeepInfer device = one logical NeuronCore, NEURON_RT_VISIBLE_CORES, NUMA from neuron-ls). - PlatformNeuron: takes the Ascend (is_npu) kernel layouts, adds is_neuron; DEEPINFER_NEURON_DEVICE=cpu runs the same code on the host for correctness work. - neuron_ops/transfer_to_neuron: map "cuda" devices, torch.device and torch.cuda.* onto neuron:0 (counterpart of torch_npu transfer_to_npu). - C++ extension: -DWITH_NEURON host-only build; torch-allocated buffers and tensor-view slot copies instead of raw device-pointer copies. - Pure-torch drop-in vendor packages (Ascend API semantics): deep_gemm, flash_mla, deep_select, tile_kernels, tilelang (constants only). - tilelang_ops/neuron backend: KV cache / metadata / norm / compress kernels; CP, ZOS and VL entry points raise NotImplementedError. - Basic mode defaults on Neuron: eager, no DSpark/MTP drafting, no zero-overhead scheduling; MoE avoids the GPU-only mega kernel; mHC prenorm GEMM uses the Ascend single-split reduction. Not yet included: deep_ep, the sampling kernels, end-to-end harness. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
46 lines
1.8 KiB
C++
46 lines
1.8 KiB
C++
#include "graph_timer.hpp"
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#include <stdexcept>
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namespace deepinfer::graph_timer {
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EventHandle::EventHandle() { throw std::runtime_error("Neuron graph timer primitives are not implemented"); }
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void EventHandle::record(int64_t stream, bool capture_external) const {
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throw std::runtime_error("Neuron graph timer primitives are not implemented");
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}
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void EventHandle::synchronize() const { throw std::runtime_error("Neuron graph timer primitives are not implemented"); }
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bool EventHandle::query() const { throw std::runtime_error("Neuron graph timer primitives are not implemented"); }
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float EventHandle::elapsed_time(const EventHandle &end_event) const {
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throw std::runtime_error("Neuron graph timer primitives are not implemented");
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}
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bool EventHandle::operator==(const EventHandle &other) const {
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throw std::runtime_error("Neuron graph timer primitives are not implemented");
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}
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std::size_t EventHandle::hash() const { throw std::runtime_error("Neuron graph timer primitives are not implemented"); }
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EventHandle EventRecordNodeHandle::get_event() const { throw std::runtime_error("Neuron graph timer primitives are not implemented"); }
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void EventRecordNodeHandle::set_event(const EventHandle &event) {
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throw std::runtime_error("Neuron graph timer primitives are not implemented");
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}
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GraphHandle::GraphHandle(py::object graph) : graph_(std::move(graph)) {}
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std::vector<EventRecordNodeHandle> GraphHandle::get_event_record_nodes() const {
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throw std::runtime_error("Neuron graph timer primitives are not implemented");
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}
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bool GraphHandle::operator==(const GraphHandle &other) const {
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throw std::runtime_error("Neuron graph timer primitives are not implemented");
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}
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std::size_t GraphHandle::hash() const { throw std::runtime_error("Neuron graph timer primitives are not implemented"); }
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} // namespace deepinfer::graph_timer
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