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* Bundle missing cudnn_engines_tensor_ir library for cuda-redist-cudnn artifact (pull #1785)
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CHANGELOG.md

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* Bundle missing `cudnn_engines_tensor_ir` library for `cuda-redist-cudnn` artifact ([pull #1785](https://github.com/bytedeco/javacpp-presets/pull/1785))
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* Add missing mappings for `c10::ArrayRef<double>` in presets for PyTorch ([issue #1770](https://github.com/bytedeco/javacpp-presets/issues/1770))
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* Reduce overhead of `Tensor` factory methods `create()`, `createBuffer()`, and `createIndexer()` for PyTorch ([issue #1770](https://github.com/bytedeco/javacpp-presets/issues/1770))
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* Enable support for OpenVINO in presets for ONNX Runtime ([pull #1769](https://github.com/bytedeco/javacpp-presets/pull/1769))

cuda/src/main/java/org/bytedeco/cuda/presets/cudnn.java

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@Properties(inherit = cublas.class, value = {
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@Platform(include = {"<cudnn.h>", "<cudnn_version.h>", "<cudnn_graph.h>", "<cudnn_ops.h>", "<cudnn_adv.h>", "<cudnn_cnn.h>", "<cudnn_backend.h>"},
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link = {"cudnn@.9", "cudnn_graph@.9", "cudnn_engines_precompiled@.9", "cudnn_engines_runtime_compiled@.9",
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"cudnn_heuristic@.9", "cudnn_ops@.9", "cudnn_adv@.9", "cudnn_cnn@.9"}),
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"cudnn_engines_tensor_ir@.9", "cudnn_heuristic@.9", "cudnn_ops@.9", "cudnn_adv@.9", "cudnn_cnn@.9"}),
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@Platform(value = "windows-x86_64", preload = {"zlibwapi", "cudnn64_9", "cudnn_graph64_9", "cudnn_engines_precompiled64_9", "cudnn_engines_runtime_compiled64_9",
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"cudnn_heuristic64_9", "cudnn_ops64_9", "cudnn_adv64_9", "cudnn_cnn64_9"})},
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target = "org.bytedeco.cuda.cudnn", global = "org.bytedeco.cuda.global.cudnn")

onnxruntime/src/main/java/org/bytedeco/onnxruntime/presets/onnxruntime.java

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}
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String[] libs = {"cudart", "cublasLt", "cublas", "cufft", "curand", "cudnn",
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"cudnn_graph", "cudnn_engines_precompiled", "cudnn_engines_runtime_compiled",
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"cudnn_heuristic", "cudnn_ops", "cudnn_adv", "cudnn_cnn"};
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"cudnn_engines_tensor_ir", "cudnn_heuristic", "cudnn_ops", "cudnn_adv", "cudnn_cnn"};
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for (String lib : libs) {
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if (platform.startsWith("linux")) {
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lib += lib.startsWith("cudnn") ? "@.9" : lib.equals("cufft") ? "@.12" : lib.equals("curand") ? "@.10" : lib.equals("cudart") ? "@.13" : "@.13";

opencv/src/main/java/org/bytedeco/opencv/presets/opencv_core.java

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String[] libs = {"cudart", "cublasLt", "cublas", "cufft", "cudnn", "nppc", "nppial", "nppicc", "nppicom",
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"nppidei", "nppif", "nppig", "nppim", "nppist", "nppisu", "nppitc", "npps",
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"cudnn_graph", "cudnn_engines_precompiled", "cudnn_engines_runtime_compiled",
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"cudnn_heuristic", "cudnn_ops", "cudnn_adv", "cudnn_cnn"};
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"cudnn_engines_tensor_ir", "cudnn_heuristic", "cudnn_ops", "cudnn_adv", "cudnn_cnn"};
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for (String lib : libs) {
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if (platform.startsWith("linux")) {
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lib += lib.startsWith("cudnn") ? "@.9" : lib.equals("cufft") ? "@.12" : lib.equals("cudart") ? "@.13" : "@.13";

pytorch/src/main/java/org/bytedeco/pytorch/presets/torch.java

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String[] libs = {"cudart", "cublasLt", "cublas", "cufft", "cupti", "curand", "nvJitLink", "cusparse", "cusolver",
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"cudnn", "cufile", "cufile_rdma", "nccl", "nvrtc", "nvrtc-builtins", "myelin", "nvinfer",
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"cudnn_graph", "cudnn_engines_precompiled", "cudnn_engines_runtime_compiled",
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"cudnn_heuristic", "cudnn_ops", "cudnn_adv", "cudnn_cnn"};
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"cudnn_engines_tensor_ir", "cudnn_heuristic", "cudnn_ops", "cudnn_adv", "cudnn_cnn"};
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for (String lib : libs) {
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if (platform.startsWith("linux")) {
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lib += lib.startsWith("cudnn") ? "@.9"

tensorrt/src/main/java/org/bytedeco/tensorrt/presets/nvinfer.java

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}
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String[] libs = {"cudart", "cublasLt", "cublas", "cudnn", "nvrtc",
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"cudnn_graph", "cudnn_engines_precompiled", "cudnn_engines_runtime_compiled",
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"cudnn_heuristic", "cudnn_ops", "cudnn_adv", "cudnn_cnn"};
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"cudnn_engines_tensor_ir", "cudnn_heuristic", "cudnn_ops", "cudnn_adv", "cudnn_cnn"};
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for (String lib : libs) {
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if (platform.startsWith("linux")) {
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lib += lib.startsWith("cudnn") ? "@.9" : lib.equals("cudart") ? "@.13" : lib.equals("nvrtc") ? "@.13" : "@.13";

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