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perf: accelerate INT8 diffusion inference with CUDA fusions (#2235)
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@@ -141,7 +141,7 @@ private:
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size_t logged_segment_count_ = 0;
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ggml_status last_compute_status_ = GGML_STATUS_SUCCESS;
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sd::ComputeWorkspace::Measurement measure(ggml_cgraph* graph, size_t direct_bytes);
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sd::ComputeWorkspace::Measurement measure(ggml_cgraph* graph);
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std::vector<DeviceMemoryRequest> memory_requests(const std::vector<sd::BackendBufferSize>& sizes,
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size_t pending_cache_bytes) const;
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bool fits(const std::vector<DeviceMemoryRequest>& requests,
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@@ -161,6 +161,7 @@ protected:
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sd::GraphCutTensorCache cut_cache_;
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sd::ComputeWorkspace workspace_;
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ggml_context* compute_ctx = nullptr;
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std::unique_ptr<std::max_align_t[]> compute_ctx_buffer_;
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bool runner_started_ = false;
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bool graph_active_ = false;
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@@ -169,7 +170,6 @@ protected:
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std::vector<size_t> graph_cut_layer_split_backend_vram_limits_;
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std::vector<ggml_backend_t> extra_runtime_backends; // borrowed (SDBackendManager-owned)
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bool multi_device_eval_callback_warned = false;
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std::shared_ptr<WeightAdapter> weight_adapter = nullptr;
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std::weak_ptr<DeviceResidencyManager> residency_manager;
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