Regenerated python docstrings
This commit is contained in:
Alejandro Saucedo
parent
b753660c29
commit
0a856c3f82
3 changed files with 481 additions and 518 deletions
3
Makefile
3
Makefile
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@ -163,6 +163,9 @@ generate_python_docstrings:
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python -m pybind11_mkdoc \
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-o python/src/docstrings.hpp \
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single_include/kompute/Kompute.hpp \
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-Iexternal/fmt/include/ \
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-Iexternal/spdlog/include/ \
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-Iexternal/glslang/ \
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-I/usr/include/c++/7.5.0/
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install_python_reqs:
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@ -28,17 +28,20 @@ R"doc(Abstraction for compute shaders that are run on top of tensors grouped
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via ParameterGroups (which group descriptorsets))doc";
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static const char *__doc_kp_Algorithm_Algorithm =
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R"doc(Base constructor for Algorithm. Should not be used unless explicit
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intended.)doc";
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static const char *__doc_kp_Algorithm_Algorithm_2 =
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R"doc(Default constructor for Algorithm
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R"doc(Main constructor for algorithm with configuration parameters to create
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the underlying resources.
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@param device The Vulkan device to use for creating resources @param
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commandBuffer The vulkan command buffer to bind the pipeline and
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shaders)doc";
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static const char *__doc_kp_Algorithm_createDescriptorPool = R"doc()doc";
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tensors (optional) The tensors to use to create the descriptor
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resources @param spirv (optional) The spirv code to use to create the
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algorithm @param workgroup (optional) The kp::Workgroup to use for the
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dispatch which defaults to kp::Workgroup(tensor[0].size(), 1, 1) if
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not set. @param specializationConstants (optional) The kp::Constants
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to use to initialize the specialization constants which cannot be
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changed once set. @param pushConstants (optional) The kp::Constants to
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use when initializing the pipeline, which set the size of the push
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constants - these can be modified but all new values must have the
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same vector size as this initial value.)doc";
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static const char *__doc_kp_Algorithm_createParameters = R"doc()doc";
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@ -46,15 +49,35 @@ static const char *__doc_kp_Algorithm_createPipeline = R"doc()doc";
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static const char *__doc_kp_Algorithm_createShaderModule = R"doc()doc";
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static const char *__doc_kp_Algorithm_init =
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R"doc(Initialiser for the shader data provided to the algorithm as well as
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tensor parameters that will be used in shader.
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static const char *__doc_kp_Algorithm_destroy = R"doc()doc";
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@param shaderFileData The bytes in spir-v format of the shader
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@tensorParams The Tensors to be used in the Algorithm / shader for
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processing)doc";
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static const char *__doc_kp_Algorithm_getPush =
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R"doc(Gets the specialization constants of the current algorithm.
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static const char *__doc_kp_Algorithm_mCommandBuffer = R"doc()doc";
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@returns The kp::Constants currently set for push constants)doc";
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static const char *__doc_kp_Algorithm_getSpecializationConstants =
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R"doc(Gets the specialization constants of the current algorithm.
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@returns The kp::Constants currently set for specialization constants)doc";
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static const char *__doc_kp_Algorithm_getTensors =
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R"doc(Gets the current tensors that are used in the algorithm.
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@returns The list of tensors used in the algorithm.)doc";
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static const char *__doc_kp_Algorithm_getWorkgroup =
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R"doc(Gets the current workgroup from the algorithm.
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@param The kp::Constant to use to set the push constants to use in the
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next bindPush(...) calls. The constants provided must be of the same
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size as the ones created during initialization.)doc";
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static const char *__doc_kp_Algorithm_isInit =
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R"doc(function that checks all the gpu resource components to verify if
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these have been created and returns true if all are valid.
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@returns returns true if the algorithm is currently initialized.)doc";
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static const char *__doc_kp_Algorithm_mDescriptorPool = R"doc()doc";
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@ -84,14 +107,70 @@ static const char *__doc_kp_Algorithm_mPipelineCache = R"doc()doc";
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static const char *__doc_kp_Algorithm_mPipelineLayout = R"doc()doc";
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static const char *__doc_kp_Algorithm_mPushConstants = R"doc()doc";
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static const char *__doc_kp_Algorithm_mShaderModule = R"doc()doc";
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static const char *__doc_kp_Algorithm_mSpecializationConstants = R"doc()doc";
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static const char *__doc_kp_Algorithm_mSpirv = R"doc()doc";
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static const char *__doc_kp_Algorithm_mTensors = R"doc()doc";
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static const char *__doc_kp_Algorithm_mWorkgroup = R"doc()doc";
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static const char *__doc_kp_Algorithm_rebuild =
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R"doc(Rebuild function to reconstruct algorithm with configuration
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parameters to create the underlying resources.
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@param tensors The tensors to use to create the descriptor resources
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@param spirv The spirv code to use to create the algorithm @param
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workgroup (optional) The kp::Workgroup to use for the dispatch which
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defaults to kp::Workgroup(tensor[0].size(), 1, 1) if not set. @param
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specializationConstants (optional) The kp::Constants to use to
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initialize the specialization constants which cannot be changed once
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set. @param pushConstants (optional) The kp::Constants to use when
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initializing the pipeline, which set the size of the push constants -
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these can be modified but all new values must have the same vector
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size as this initial value.)doc";
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static const char *__doc_kp_Algorithm_recordBindCore =
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R"doc(Records command that binds the "core" algorithm components which
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consist of binding the pipeline and binding the descriptorsets.
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@param commandBuffer Command buffer to record the algorithm resources
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to)doc";
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static const char *__doc_kp_Algorithm_recordBindPush =
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R"doc(Records command that binds the push constants to the command buffer
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provided - it is required that the pushConstants provided are of the
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same size as the ones provided during initialization.
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@param commandBuffer Command buffer to record the algorithm resources
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to)doc";
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static const char *__doc_kp_Algorithm_recordDispatch =
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R"doc(Records the dispatch function with the provided template parameters or
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alternatively using the size of the tensor by default.
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@param x Layout X dispatch value @param y Layout Y dispatch value
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@param z Layout Z dispatch value)doc";
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@param commandBuffer Command buffer to record the algorithm resources
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to)doc";
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static const char *__doc_kp_Algorithm_setPush =
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R"doc(Sets the push constants to the new value provided to use in the next
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bindPush()
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@param The kp::Constant to use to set the push constants to use in the
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next bindPush(...) calls. The constants provided must be of the same
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size as the ones created during initialization.)doc";
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static const char *__doc_kp_Algorithm_setWorkgroup =
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R"doc(Sets the work group to use in the recordDispatch
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@param workgroup The kp::Workgroup value to use to update the
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algorithm. It must have a value greater than 1 on the x value (index
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1) otherwise it will be initialized on the size of the first tensor
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(ie. this->mTensor[0]->size()))doc";
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static const char *__doc_kp_Manager =
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R"doc(Base orchestrator which creates and manages device and child
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@ -102,13 +181,13 @@ R"doc(Base constructor and default used which creates the base resources
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including choosing the device 0 by default.)doc";
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static const char *__doc_kp_Manager_Manager_2 =
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R"doc(Similar to base constructor but allows the user to provide the device
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they would like to create the resources on.
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R"doc(Similar to base constructor but allows for further configuration to
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use when creating the Vulkan resources.
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@param physicalDeviceIndex The index of the physical device to use
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@param familyQueueIndices (Optional) List of queue indices to add for
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explicit allocation @param totalQueues The total number of compute
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queues to create.)doc";
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explicit allocation @param desiredExtensions The desired extensions to
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load from physicalDevice)doc";
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static const char *__doc_kp_Manager_Manager_3 =
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R"doc(Manager constructor which allows your own vulkan application to
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@ -119,99 +198,33 @@ integrate with the vulkan kompute use.
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@param device Vulkan logical device to use for all base resources
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@param physicalDeviceIndex Index for vulkan physical device used)doc";
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static const char *__doc_kp_Manager_algorithm =
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R"doc(Create a managed algorithm that will be destroyed by this manager if
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it hasn't been destroyed by its reference count going to zero.
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@param tensors (optional) The tensors to initialise the algorithm with
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@param spirv (optional) The SPIRV bytes for the algorithm to dispatch
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@param workgroup (optional) kp::Workgroup for algorithm to use, and
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defaults to (tensor[0].size(), 1, 1) @param specializationConstants
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(optional) kp::Constant to use for specialization constants, and
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defaults to an empty constant @param pushConstants (optional)
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kp::Constant to use for push constants, and defaults to an empty
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constant @returns Shared pointer with initialised algorithm)doc";
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static const char *__doc_kp_Manager_clear =
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R"doc(Run a pseudo-garbage collection to release all the managed resources
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that have been already freed due to these reaching to zero ref count.)doc";
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static const char *__doc_kp_Manager_createDevice = R"doc()doc";
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static const char *__doc_kp_Manager_createInstance = R"doc()doc";
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static const char *__doc_kp_Manager_destroy =
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R"doc(Destroy owned Vulkan GPU resources and free GPU memory for single
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tensor.
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@param tensors Single tensor to rebuild)doc";
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static const char *__doc_kp_Manager_destroy_2 =
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R"doc(Destroy owned Vulkan GPU resources and free GPU memory for vector of
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tensors.
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@param tensors Single tensor to rebuild)doc";
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static const char *__doc_kp_Manager_destroy_3 =
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R"doc(Destroy owned Vulkan GPU resources and free GPU memory for vector of
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sequences. Destroying by sequence name is more efficent and hence
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recommended instead of by object.
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@param sequences Vector for shared ptrs with sequences to destroy)doc";
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static const char *__doc_kp_Manager_destroy_4 =
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R"doc(Destroy owned Vulkan GPU resources and free GPU memory for single
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sequence. Destroying by sequence name is more efficent and hence
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recommended instead of by object.
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@param sequences Single sequence to rebuild)doc";
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static const char *__doc_kp_Manager_destroy_5 =
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R"doc(Destroy owned Vulkan GPU resources and free GPU memory for sequence by
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name.
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@param sequenceName Single name of named sequence to destroy)doc";
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static const char *__doc_kp_Manager_destroy_6 =
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R"doc(Destroy owned Vulkan GPU resources and free GPU memory for sequences
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using vector of named sequence names.
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@param sequenceName Vector of sequence names to destroy)doc";
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static const char *__doc_kp_Manager_evalOp =
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R"doc(Function that evaluates operation against named sequence.
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@param tensors The tensors to be used in the operation recorded @param
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sequenceName The name of the sequence to be retrieved or created
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@param TArgs Template parameters that will be used to initialise
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Operation to allow for extensible configurations on initialisation)doc";
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static const char *__doc_kp_Manager_evalOpAsync =
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R"doc(Function that evaluates operation against named sequence
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asynchronously.
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@param tensors The tensors to be used in the operation recorded @param
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sequenceName The name of the sequence to be retrieved or created
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@param params Template parameters that will be used to initialise
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Operation to allow for extensible configurations on initialisation)doc";
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static const char *__doc_kp_Manager_evalOpAsyncDefault =
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R"doc(Operation that evaluates operation against default sequence
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asynchronously.
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@param tensors The tensors to be used in the operation recorded @param
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params Template parameters that will be used to initialise Operation
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to allow for extensible configurations on initialisation)doc";
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static const char *__doc_kp_Manager_evalOpAwait =
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R"doc(Operation that awaits for named sequence to finish.
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@param sequenceName The name of the sequence to wait for termination
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@param waitFor The amount of time to wait before timing out)doc";
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static const char *__doc_kp_Manager_evalOpAwaitDefault =
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R"doc(Operation that awaits for default sequence to finish.
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@param tensors The tensors to be used in the operation recorded @param
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params Template parameters that will be used to initialise Operation
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to allow for extensible configurations on initialisation)doc";
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static const char *__doc_kp_Manager_evalOpDefault =
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R"doc(Function that evaluates operation against a newly created sequence.
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@param tensors The tensors to be used in the operation recorded @param
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TArgs Template parameters that will be used to initialise Operation to
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allow for extensible configurations on initialisation)doc";
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static const char *__doc_kp_Manager_destroy = R"doc(Destroy the GPU resources and all managed resources by manager.)doc";
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static const char *__doc_kp_Manager_mComputeQueueFamilyIndices = R"doc()doc";
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static const char *__doc_kp_Manager_mComputeQueues = R"doc()doc";
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static const char *__doc_kp_Manager_mCurrentSequenceIndex = R"doc()doc";
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static const char *__doc_kp_Manager_mDevice = R"doc()doc";
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static const char *__doc_kp_Manager_mFreeDevice = R"doc()doc";
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@ -220,190 +233,51 @@ static const char *__doc_kp_Manager_mFreeInstance = R"doc()doc";
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static const char *__doc_kp_Manager_mInstance = R"doc()doc";
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static const char *__doc_kp_Manager_mManageResources = R"doc()doc";
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static const char *__doc_kp_Manager_mManagedAlgorithms = R"doc()doc";
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static const char *__doc_kp_Manager_mManagedSequences = R"doc()doc";
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static const char *__doc_kp_Manager_mManagedTensors = R"doc()doc";
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static const char *__doc_kp_Manager_mPhysicalDevice = R"doc()doc";
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static const char *__doc_kp_Manager_mPhysicalDeviceIndex = R"doc()doc";
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static const char *__doc_kp_Manager_rebuild =
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R"doc(Function that simplifies the common workflow of tensor initialisation.
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It will take the constructor parameters for a Tensor and will will us
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it to create a new Tensor. The tensor memory will then be managed and
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owned by the manager.
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@param tensors Array of tensors to rebuild @param syncDataToGPU
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Whether to sync the data to GPU memory)doc";
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static const char *__doc_kp_Manager_rebuild_2 =
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R"doc(Function that simplifies the common workflow of tensor initialisation.
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It will take the constructor parameters for a Tensor and will will us
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it to create a new Tensor. The tensor memory will then be managed and
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owned by the manager.
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@param tensors Single tensor to rebuild @param syncDataToGPU Whether
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to sync the data to GPU memory)doc";
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static const char *__doc_kp_Manager_sequence =
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R"doc(Get or create a managed Sequence that will be contained by this
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manager. If the named sequence does not currently exist, it would be
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created and initialised.
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R"doc(Create a managed sequence that will be destroyed by this manager if it
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hasn't been destroyed by its reference count going to zero.
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@param sequenceName The name for the named sequence to be retrieved or
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created @param queueIndex The queue to use from the available queues
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@return Shared pointer to the manager owned sequence resource)doc";
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@param queueIndex The queue to use from the available queues @returns
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Shared pointer with initialised sequence)doc";
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static const char *__doc_kp_Manager_tensor =
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R"doc(Function that simplifies the common workflow of tensor creation and
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initialization. It will take the constructor parameters for a Tensor
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and will will us it to create a new Tensor and then create it. The
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tensor memory will then be managed and owned by the manager.
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R"doc(Create a managed tensor that will be destroyed by this manager if it
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hasn't been destroyed by its reference count going to zero.
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@param data The data to initialize the tensor with @param tensorType
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The type of tensor to initialize @param syncDataToGPU Whether to sync
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the data to GPU memory @returns Initialized Tensor with memory Syncd
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to GPU device)doc";
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The type of tensor to initialize @returns Shared pointer with
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initialised tensor)doc";
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static const char *__doc_kp_OpAlgoCreate =
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static const char *__doc_kp_OpAlgoDispatch =
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R"doc(Operation that provides a general abstraction that simplifies the use
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of algorithm and parameter components which can be used with shaders.
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By default it enables the user to provide a dynamic number of tensors
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which are then passed as inputs.)doc";
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static const char *__doc_kp_OpAlgoCreate_KomputeWorkgroup = R"doc()doc";
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static const char *__doc_kp_OpAlgoDispatch_OpAlgoDispatch = R"doc()doc";
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static const char *__doc_kp_OpAlgoCreate_KomputeWorkgroup_x = R"doc()doc";
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static const char *__doc_kp_OpAlgoDispatch_mAlgorithm = R"doc()doc";
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static const char *__doc_kp_OpAlgoCreate_KomputeWorkgroup_y = R"doc()doc";
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static const char *__doc_kp_OpAlgoDispatch_mPushConstants = R"doc()doc";
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static const char *__doc_kp_OpAlgoCreate_KomputeWorkgroup_z = R"doc()doc";
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static const char *__doc_kp_OpAlgoCreate_OpAlgoCreate = R"doc(Base constructor, should not be used unless explicitly intended.)doc";
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static const char *__doc_kp_OpAlgoCreate_OpAlgoCreate_2 =
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R"doc(Default constructor with parameters that provides the bare minimum
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requirements for the operations to be able to create and manage their
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sub-components.
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@param physicalDevice Vulkan physical device used to find device
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queues @param device Vulkan logical device for passing to Algorithm
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@param commandBuffer Vulkan Command Buffer to record commands into
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@param tensors Tensors that are to be used in this operation @param
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shaderFilePath Optional parameter to specify the shader to load
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(either in spirv or raw format) @param komputeWorkgroup Optional
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parameter to specify the layout for processing)doc";
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static const char *__doc_kp_OpAlgoCreate_OpAlgoCreate_3 =
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R"doc(Constructor that enables a file to be passed to the operation with the
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contents of the shader. This can be either in raw format or in
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compiled SPIR-V binary format.
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@param physicalDevice Vulkan physical device used to find device
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queues @param device Vulkan logical device for passing to Algorithm
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@param commandBuffer Vulkan Command Buffer to record commands into
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@param tensors Tensors that are to be used in this operation @param
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shaderFilePath Parameter to specify the shader to load (either in
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spirv or raw format) @param komputeWorkgroup Optional parameter to
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specify the layout for processing)doc";
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static const char *__doc_kp_OpAlgoCreate_OpAlgoCreate_4 =
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R"doc(Constructor that enables raw shader data to be passed to the main
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operation which can be either in raw shader glsl code or in compiled
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SPIR-V binary.
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@param physicalDevice Vulkan physical device used to find device
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queues @param device Vulkan logical device for passing to Algorithm
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@param commandBuffer Vulkan Command Buffer to record commands into
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@param tensors Tensors that are to be used in this operation @param
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shaderDataRaw Optional parameter to specify the shader data either in
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binary or raw form @param komputeWorkgroup Optional parameter to
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specify the layout for processing)doc";
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static const char *__doc_kp_OpAlgoCreate_fetchSpirvBinaryData = R"doc()doc";
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static const char *__doc_kp_OpAlgoCreate_init =
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R"doc(The init function is responsible for the initialisation of the
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algorithm component based on the parameters specified, and allows for
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extensibility on the options provided. Further dependent classes can
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perform more specific checks such as ensuring tensors provided are
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initialised, etc.)doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoCreate_mAlgorithm = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoCreate_mFreeAlgorithm = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoCreate_mKomputeWorkgroup = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoCreate_mShaderDataRaw =
|
||||
R"doc(< Optional member variable which can be provided to contain either the
|
||||
raw shader content or the spirv binary content)doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoCreate_mShaderFilePath =
|
||||
R"doc(< Optional member variable which can be provided for the OpAlgoCreate to
|
||||
find the data automatically and load for processing)doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoCreate_postEval =
|
||||
static const char *__doc_kp_OpAlgoDispatch_postEval =
|
||||
R"doc(Executes after the recorded commands are submitted, and performs a
|
||||
copy of the GPU Device memory into the staging buffer so the output
|
||||
data can be retrieved.)doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoCreate_preEval = R"doc(Does not perform any preEval commands.)doc";
|
||||
static const char *__doc_kp_OpAlgoDispatch_preEval = R"doc(Does not perform any preEval commands.)doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoCreate_record =
|
||||
R"doc(This records the commands that are to be sent to the GPU. This
|
||||
includes the barriers that ensure the memory has been copied before
|
||||
going in and out of the shader, as well as the dispatch operation that
|
||||
sends the shader processing to the gpu. This function also records the
|
||||
GPU memory copy of the output data for the staging buffer so it can be
|
||||
read by the host.)doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoLhsRhsOut =
|
||||
R"doc(Operation base class to simplify the creation of operations that
|
||||
require right hand and left hand side datapoints together with a
|
||||
single output. The expected data passed is two input tensors and one
|
||||
output tensor.)doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoLhsRhsOut_OpAlgoLhsRhsOut = R"doc(Base constructor, should not be used unless explicitly intended.)doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoLhsRhsOut_OpAlgoLhsRhsOut_2 =
|
||||
R"doc(Default constructor with parameters that provides the bare minimum
|
||||
requirements for the operations to be able to create and manage their
|
||||
sub-components.
|
||||
|
||||
@param physicalDevice Vulkan physical device used to find device
|
||||
queues @param device Vulkan logical device for passing to Algorithm
|
||||
@param commandBuffer Vulkan Command Buffer to record commands into
|
||||
@param tensors Tensors that are to be used in this operation @param
|
||||
freeTensors Whether operation manages the memory of the Tensors @param
|
||||
komputeWorkgroup Optional parameter to specify the layout for
|
||||
processing)doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoLhsRhsOut_init =
|
||||
R"doc(The init function is responsible for ensuring that all of the tensors
|
||||
provided are aligned with requirements such as LHS, RHS and Output
|
||||
tensors, and creates the algorithm component which processes the
|
||||
computation.)doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoLhsRhsOut_mTensorLHS =
|
||||
R"doc(< Reference to the parameter used in the left hand side equation of
|
||||
the shader)doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoLhsRhsOut_mTensorOutput =
|
||||
R"doc(< Reference to the parameter used in the output of the shader and will
|
||||
be copied with a staging vector)doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoLhsRhsOut_mTensorRHS =
|
||||
R"doc(< Reference to the parameter used in the right hand side equation of
|
||||
the shader)doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoLhsRhsOut_postEval =
|
||||
R"doc(Executes after the recorded commands are submitted, and performs a
|
||||
copy of the GPU Device memory into the staging buffer so the output
|
||||
data can be retrieved.)doc";
|
||||
|
||||
static const char *__doc_kp_OpAlgoLhsRhsOut_record =
|
||||
static const char *__doc_kp_OpAlgoDispatch_record =
|
||||
R"doc(This records the commands that are to be sent to the GPU. This
|
||||
includes the barriers that ensure the memory has been copied before
|
||||
going in and out of the shader, as well as the dispatch operation that
|
||||
|
|
@ -419,36 +293,6 @@ Operations can perform actions on tensors, and optionally can also own
|
|||
an Algorithm with respective parameters. kp::Operations with
|
||||
kp::Algorithms would inherit from kp::OpBaseAlgo.)doc";
|
||||
|
||||
static const char *__doc_kp_OpBase_OpBase = R"doc(Base constructor, should not be used unless explicitly intended.)doc";
|
||||
|
||||
static const char *__doc_kp_OpBase_OpBase_2 =
|
||||
R"doc(Default constructor with parameters that provides the bare minimum
|
||||
requirements for the operations to be able to create and manage their
|
||||
sub-components.
|
||||
|
||||
@param physicalDevice Vulkan physical device used to find device
|
||||
queues @param device Vulkan logical device for passing to Algorithm
|
||||
@param commandBuffer Vulkan Command Buffer to record commands into
|
||||
@param tensors Tensors that are to be used in this operation)doc";
|
||||
|
||||
static const char *__doc_kp_OpBase_init =
|
||||
R"doc(The init function is responsible for setting up all the resources and
|
||||
should be called after the Operation has been created.)doc";
|
||||
|
||||
static const char *__doc_kp_OpBase_mCommandBuffer = R"doc(< Vulkan Command Buffer)doc";
|
||||
|
||||
static const char *__doc_kp_OpBase_mDevice = R"doc(< Vulkan Logical Device)doc";
|
||||
|
||||
static const char *__doc_kp_OpBase_mFreeTensors =
|
||||
R"doc(< Explicit boolean that specifies whether the < tensors are freed (if
|
||||
they are managed))doc";
|
||||
|
||||
static const char *__doc_kp_OpBase_mPhysicalDevice = R"doc(< Vulkan Physical Device)doc";
|
||||
|
||||
static const char *__doc_kp_OpBase_mTensors =
|
||||
R"doc(< Tensors referenced by operation that can be managed < optionally by
|
||||
operation)doc";
|
||||
|
||||
static const char *__doc_kp_OpBase_postEval =
|
||||
R"doc(Post eval is called after the Sequence has called eval and submitted
|
||||
the commands to the GPU for processing, and can be used to perform any
|
||||
|
|
@ -474,9 +318,7 @@ static const char *__doc_kp_OpMult =
|
|||
R"doc(Operation that performs multiplication on two tensors and outpus on
|
||||
third tensor.)doc";
|
||||
|
||||
static const char *__doc_kp_OpMult_OpMult = R"doc(Base constructor, should not be used unless explicitly intended.)doc";
|
||||
|
||||
static const char *__doc_kp_OpMult_OpMult_2 =
|
||||
static const char *__doc_kp_OpMult_OpMult =
|
||||
R"doc(Default constructor with parameters that provides the bare minimum
|
||||
requirements for the operations to be able to create and manage their
|
||||
sub-components.
|
||||
|
|
@ -494,9 +336,7 @@ the tensors provided, using a record command for all the vectors. This
|
|||
operation does not own/manage the memory of the tensors passed to it.
|
||||
The operation must only receive tensors of type)doc";
|
||||
|
||||
static const char *__doc_kp_OpTensorCopy_OpTensorCopy = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_OpTensorCopy_OpTensorCopy_2 =
|
||||
static const char *__doc_kp_OpTensorCopy_OpTensorCopy =
|
||||
R"doc(Default constructor with parameters that provides the core vulkan
|
||||
resources and the tensors that will be used in the operation.
|
||||
|
||||
|
|
@ -505,10 +345,7 @@ queues @param device Vulkan logical device for passing to Algorithm
|
|||
@param commandBuffer Vulkan Command Buffer to record commands into
|
||||
@param tensors Tensors that will be used to create in operation.)doc";
|
||||
|
||||
static const char *__doc_kp_OpTensorCopy_init =
|
||||
R"doc(Performs basic checks such as ensuring there are at least two tensors
|
||||
provided, that they are initialised and that they are not of type
|
||||
TensorTypes::eStorage.)doc";
|
||||
static const char *__doc_kp_OpTensorCopy_mTensors = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_OpTensorCopy_postEval =
|
||||
R"doc(Copies the local vectors for all the tensors to sync the data with the
|
||||
|
|
@ -530,9 +367,7 @@ will happen during preEval before the recorded commands are
|
|||
dispatched. This operation won't have any effect on
|
||||
TensorTypes::eStaging.)doc";
|
||||
|
||||
static const char *__doc_kp_OpTensorSyncDevice_OpTensorSyncDevice = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_OpTensorSyncDevice_OpTensorSyncDevice_2 =
|
||||
static const char *__doc_kp_OpTensorSyncDevice_OpTensorSyncDevice =
|
||||
R"doc(Default constructor with parameters that provides the core vulkan
|
||||
resources and the tensors that will be used in the operation. The
|
||||
tensos provided cannot be of type TensorTypes::eStorage.
|
||||
|
|
@ -542,9 +377,7 @@ queues @param device Vulkan logical device for passing to Algorithm
|
|||
@param commandBuffer Vulkan Command Buffer to record commands into
|
||||
@param tensors Tensors that will be used to create in operation.)doc";
|
||||
|
||||
static const char *__doc_kp_OpTensorSyncDevice_init =
|
||||
R"doc(Performs basic checks such as ensuring that there is at least one
|
||||
tensor provided with min memory of 1 element.)doc";
|
||||
static const char *__doc_kp_OpTensorSyncDevice_mTensors = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_OpTensorSyncDevice_postEval = R"doc(Does not perform any postEval commands.)doc";
|
||||
|
||||
|
|
@ -564,9 +397,7 @@ will happen during preEval before the recorded commands are
|
|||
dispatched. This operation won't have any effect on
|
||||
TensorTypes::eStaging.)doc";
|
||||
|
||||
static const char *__doc_kp_OpTensorSyncLocal_OpTensorSyncLocal = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_OpTensorSyncLocal_OpTensorSyncLocal_2 =
|
||||
static const char *__doc_kp_OpTensorSyncLocal_OpTensorSyncLocal =
|
||||
R"doc(Default constructor with parameters that provides the core vulkan
|
||||
resources and the tensors that will be used in the operation. The
|
||||
tensors provided cannot be of type TensorTypes::eStorage.
|
||||
|
|
@ -576,9 +407,7 @@ queues @param device Vulkan logical device for passing to Algorithm
|
|||
@param commandBuffer Vulkan Command Buffer to record commands into
|
||||
@param tensors Tensors that will be used to create in operation.)doc";
|
||||
|
||||
static const char *__doc_kp_OpTensorSyncLocal_init =
|
||||
R"doc(Performs basic checks such as ensuring that there is at least one
|
||||
tensor provided with min memory of 1 element.)doc";
|
||||
static const char *__doc_kp_OpTensorSyncLocal_mTensors = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_OpTensorSyncLocal_postEval =
|
||||
R"doc(For host tensors it performs the map command from the host memory into
|
||||
|
|
@ -593,10 +422,6 @@ the data from its device to staging memory.)doc";
|
|||
static const char *__doc_kp_Sequence = R"doc(Container of operations that can be sent to GPU as batch)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_Sequence =
|
||||
R"doc(Base constructor for Sequence. Should not be used unless explicit
|
||||
intended.)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_Sequence_2 =
|
||||
R"doc(Main constructor for sequence which requires core vulkan components to
|
||||
generate all dependent resources.
|
||||
|
||||
|
|
@ -610,10 +435,18 @@ command buffer.
|
|||
|
||||
@return Boolean stating whether execution was successful.)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_clear =
|
||||
R"doc(Clear function clears all operations currently recorded and starts
|
||||
recording again.)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_createCommandBuffer = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_createCommandPool = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_destroy =
|
||||
R"doc(Destroys and frees the GPU resources which include the buffer and
|
||||
memory and sets the sequence as init=False.)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_end =
|
||||
R"doc(Ends the recording and stops recording commands when the record
|
||||
command is sent.
|
||||
|
|
@ -622,36 +455,84 @@ command is sent.
|
|||
|
||||
static const char *__doc_kp_Sequence_eval =
|
||||
R"doc(Eval sends all the recorded and stored operations in the vector of
|
||||
operations into the gpu as a submit job synchronously (with a
|
||||
barrier).
|
||||
|
||||
@return shared_ptr<Sequence> of the Sequence class itself)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_eval_2 =
|
||||
R"doc(Resets all the recorded and stored operations, records the operation
|
||||
provided and submits into the gpu as a submit job synchronously (with
|
||||
a barrier).
|
||||
|
||||
@return shared_ptr<Sequence> of the Sequence class itself)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_eval_3 =
|
||||
R"doc(Eval sends all the recorded and stored operations in the vector of
|
||||
operations into the gpu as a submit job with a barrier.
|
||||
|
||||
@return Boolean stating whether execution was successful.)doc";
|
||||
@param tensors Vector of tensors to use for the operation @param TArgs
|
||||
Template parameters that are used to initialise operation which allows
|
||||
for extensible configurations on initialisation. @return
|
||||
shared_ptr<Sequence> of the Sequence class itself)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_eval_4 =
|
||||
R"doc(Eval sends all the recorded and stored operations in the vector of
|
||||
operations into the gpu as a submit job with a barrier.
|
||||
|
||||
@param algorithm Algorithm to use for the record often used for OpAlgo
|
||||
operations @param TArgs Template parameters that are used to
|
||||
initialise operation which allows for extensible configurations on
|
||||
initialisation. @return shared_ptr<Sequence> of the Sequence class
|
||||
itself)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_evalAsync =
|
||||
R"doc(Eval Async sends all the recorded and stored operations in the vector
|
||||
of operations into the gpu as a submit job with a barrier. EvalAwait()
|
||||
must be called after to ensure the sequence is terminated correctly.
|
||||
of operations into the gpu as a submit job without a barrier.
|
||||
EvalAwait() must ALWAYS be called after to ensure the sequence is
|
||||
terminated correctly.
|
||||
|
||||
@return Boolean stating whether execution was successful.)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_evalAsync_2 =
|
||||
R"doc(Clears currnet operations to record provided one in the vector of
|
||||
operations into the gpu as a submit job without a barrier. EvalAwait()
|
||||
must ALWAYS be called after to ensure the sequence is terminated
|
||||
correctly.
|
||||
|
||||
@return Boolean stating whether execution was successful.)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_evalAsync_3 =
|
||||
R"doc(Eval sends all the recorded and stored operations in the vector of
|
||||
operations into the gpu as a submit job with a barrier.
|
||||
|
||||
@param tensors Vector of tensors to use for the operation @param TArgs
|
||||
Template parameters that are used to initialise operation which allows
|
||||
for extensible configurations on initialisation. @return
|
||||
shared_ptr<Sequence> of the Sequence class itself)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_evalAsync_4 =
|
||||
R"doc(Eval sends all the recorded and stored operations in the vector of
|
||||
operations into the gpu as a submit job with a barrier.
|
||||
|
||||
@param algorithm Algorithm to use for the record often used for OpAlgo
|
||||
operations @param TArgs Template parameters that are used to
|
||||
initialise operation which allows for extensible configurations on
|
||||
initialisation. @return shared_ptr<Sequence> of the Sequence class
|
||||
itself)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_evalAwait =
|
||||
R"doc(Eval Await waits for the fence to finish processing and then once it
|
||||
finishes, it runs the postEval of all operations.
|
||||
|
||||
@param waitFor Number of milliseconds to wait before timing out.
|
||||
@return Boolean stating whether execution was successful.)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_freeMemoryDestroyGPUResources =
|
||||
R"doc(Destroys and frees the GPU resources which include the buffer and
|
||||
memory and sets the sequence as init=False.)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_init =
|
||||
R"doc(Initialises sequence including the creation of the command pool and
|
||||
the command buffer.)doc";
|
||||
@return shared_ptr<Sequence> of the Sequence class itself)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_isInit =
|
||||
R"doc(Returns true if the sequence has been successfully initialised.
|
||||
R"doc(Returns true if the sequence has been initialised, and it's based on
|
||||
the GPU resources being refrenced.
|
||||
|
||||
@return Boolean stating if sequence has been initialised.)doc";
|
||||
@return Boolean stating if is initialized)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_isRecording =
|
||||
R"doc(Returns true if the sequence is currently in recording activated.
|
||||
|
|
@ -678,8 +559,6 @@ static const char *__doc_kp_Sequence_mFreeCommandBuffer = R"doc()doc";
|
|||
|
||||
static const char *__doc_kp_Sequence_mFreeCommandPool = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_mIsInit = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_mIsRunning = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_mOperations = R"doc()doc";
|
||||
|
|
@ -696,9 +575,66 @@ This template requires classes to be derived from the OpBase class.
|
|||
This function also requires the Sequence to be recording, otherwise it
|
||||
will not be able to add the operation.
|
||||
|
||||
@param op Object derived from kp::BaseOp that will be recoreded by the
|
||||
sequence which will be used when the operation is evaluated. @return
|
||||
shared_ptr<Sequence> of the Sequence class itself)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_record_2 =
|
||||
R"doc(Record function for operation to be added to the GPU queue in batch.
|
||||
This template requires classes to be derived from the OpBase class.
|
||||
This function also requires the Sequence to be recording, otherwise it
|
||||
will not be able to add the operation.
|
||||
|
||||
@param tensors Vector of tensors to use for the operation @param TArgs
|
||||
Template parameters that are used to initialise operation which allows
|
||||
for extensible configurations on initialisation.)doc";
|
||||
for extensible configurations on initialisation. @return
|
||||
shared_ptr<Sequence> of the Sequence class itself)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_record_3 =
|
||||
R"doc(Record function for operation to be added to the GPU queue in batch.
|
||||
This template requires classes to be derived from the OpBase class.
|
||||
This function also requires the Sequence to be recording, otherwise it
|
||||
will not be able to add the operation.
|
||||
|
||||
@param algorithm Algorithm to use for the record often used for OpAlgo
|
||||
operations @param TArgs Template parameters that are used to
|
||||
initialise operation which allows for extensible configurations on
|
||||
initialisation. @return shared_ptr<Sequence> of the Sequence class
|
||||
itself)doc";
|
||||
|
||||
static const char *__doc_kp_Sequence_rerecord =
|
||||
R"doc(Clears command buffer and triggers re-record of all the current
|
||||
operations saved, which is useful if the underlying kp::Tensors or
|
||||
kp::Algorithms are modified and need to be re-recorded.)doc";
|
||||
|
||||
static const char *__doc_kp_Shader = R"doc(Shader utily class with functions to compile and process glsl files.)doc";
|
||||
|
||||
static const char *__doc_kp_Shader_compile_source =
|
||||
R"doc(Compile a single glslang source from string value. Currently this
|
||||
function uses the glslang C++ interface which is not thread safe so
|
||||
this funciton should not be called from multiple threads concurrently.
|
||||
If you have a online shader processing multithreading use-case that
|
||||
can't use offline compilation please open an issue.
|
||||
|
||||
@param source An individual raw glsl shader in string format @param
|
||||
entryPoint The function name to use as entry point @param definitions
|
||||
List of pairs containing key value definitions @param resourcesLimit A
|
||||
list that contains the resource limits for the GLSL compiler @return
|
||||
The compiled SPIR-V binary in unsigned int32 format)doc";
|
||||
|
||||
static const char *__doc_kp_Shader_compile_sources =
|
||||
R"doc(Compile multiple sources with optional filenames. Currently this
|
||||
function uses the glslang C++ interface which is not thread safe so
|
||||
this funciton should not be called from multiple threads concurrently.
|
||||
If you have a online shader processing multithreading use-case that
|
||||
can't use offline compilation please open an issue.
|
||||
|
||||
@param sources A list of raw glsl shaders in string format @param
|
||||
files A list of file names respective to each of the sources @param
|
||||
entryPoint The function name to use as entry point @param definitions
|
||||
List of pairs containing key value definitions @param resourcesLimit A
|
||||
list that contains the resource limits for the GLSL compiler @return
|
||||
The compiled SPIR-V binary in unsigned int32 format)doc";
|
||||
|
||||
static const char *__doc_kp_Tensor =
|
||||
R"doc(Structured data used in GPU operations.
|
||||
|
|
@ -708,9 +644,7 @@ across GPUs. Each tensor would have a respective Vulkan memory and
|
|||
buffer, which would be used to store their respective data. The
|
||||
tensors can be used for GPU data storage or transfer.)doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_Tensor = R"doc(Base constructor, should not be used unless explicitly intended.)doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_Tensor_2 =
|
||||
static const char *__doc_kp_Tensor_Tensor =
|
||||
R"doc(Default constructor with data provided which would be used to create
|
||||
the respective vulkan buffer and memory.
|
||||
|
||||
|
|
@ -741,8 +675,6 @@ without exposing it.
|
|||
|
||||
@return Descriptor buffer info with own buffer)doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_copyBuffer = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_createBuffer = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_data =
|
||||
|
|
@ -753,7 +685,7 @@ memory.
|
|||
@return Reference to vector of elements representing the data in the
|
||||
tensor.)doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_freeMemoryDestroyGPUResources =
|
||||
static const char *__doc_kp_Tensor_destroy =
|
||||
R"doc(Destroys and frees the GPU resources which include the buffer and
|
||||
memory.)doc";
|
||||
|
||||
|
|
@ -765,17 +697,7 @@ static const char *__doc_kp_Tensor_getStagingBufferUsageFlags = R"doc()doc";
|
|||
|
||||
static const char *__doc_kp_Tensor_getStagingMemoryPropertyFlags = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_init =
|
||||
R"doc(Initialiser which calls the initialisation for all the respective
|
||||
tensors as well as creates the respective staging tensors. The staging
|
||||
tensors would only be created for the tensors of type
|
||||
TensorType::eDevice as otherwise there is no need to copy from host
|
||||
memory.)doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_isInit =
|
||||
R"doc(Returns true if the tensor initialisation function has been carried
|
||||
out successful, which would mean that the buffer and memory will have
|
||||
been provisioned.)doc";
|
||||
static const char *__doc_kp_Tensor_isInit = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_mData = R"doc()doc";
|
||||
|
||||
|
|
@ -789,16 +711,12 @@ static const char *__doc_kp_Tensor_mFreeStagingBuffer = R"doc()doc";
|
|||
|
||||
static const char *__doc_kp_Tensor_mFreeStagingMemory = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_mIsInit = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_mPhysicalDevice = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_mPrimaryBuffer = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_mPrimaryMemory = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_mShape = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_mStagingBuffer = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_mStagingMemory = R"doc()doc";
|
||||
|
|
@ -823,6 +741,13 @@ vector's.
|
|||
@param i The index where the element will be returned from. @return
|
||||
Returns the element in the position requested.)doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_rebuild =
|
||||
R"doc(Initialiser which calls the initialisation for all the respective
|
||||
tensors as well as creates the respective staging tensors. The staging
|
||||
tensors would only be created for the tensors of type
|
||||
TensorType::eDevice as otherwise there is no need to copy from host
|
||||
memory.)doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_recordBufferMemoryBarrier =
|
||||
R"doc(Records the buffer memory barrier into the command buffer which
|
||||
ensures that relevant data transfers are carried out correctly.
|
||||
|
|
@ -833,6 +758,8 @@ dstAccessMask Access flags for destination access mask @param
|
|||
scrStageMask Pipeline stage flags for source stage mask @param
|
||||
dstStageMask Pipeline stage flags for destination stage mask)doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_recordCopyBuffer = R"doc()doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_recordCopyFrom =
|
||||
R"doc(Records a copy from the memory of the tensor provided to the current
|
||||
thensor. This is intended to pass memory into a processing, to perform
|
||||
|
|
@ -865,13 +792,6 @@ static const char *__doc_kp_Tensor_setData =
|
|||
R"doc(Sets / resets the vector data of the tensor. This function does not
|
||||
perform any copies into GPU memory and is only performed on the host.)doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_shape =
|
||||
R"doc(Returns the shape of the tensor, which includes the number of
|
||||
dimensions and the size per dimension.
|
||||
|
||||
@return Array containing the sizes for each dimension. Zero means
|
||||
respective dimension is not active.)doc";
|
||||
|
||||
static const char *__doc_kp_Tensor_size =
|
||||
R"doc(Returns the size/magnitude of the Tensor, which will be the total
|
||||
number of elements across all dimensions
|
||||
|
|
|
|||
|
|
@ -735,124 +735,18 @@ extern py::object kp_debug, kp_info, kp_warning, kp_error;
|
|||
|
||||
namespace kp {
|
||||
|
||||
// The default resource limit for the GLSL compiler, can be overwritten
|
||||
// Has been adobted by:
|
||||
// https://github.com/KhronosGroup/glslang/blob/master/StandAlone/ResourceLimits.cpp
|
||||
const TBuiltInResource defaultResource = {
|
||||
/* .MaxLights = */ 0,
|
||||
/* .MaxClipPlanes = */ 0,
|
||||
/* .MaxTextureUnits = */ 0,
|
||||
/* .MaxTextureCoords = */ 0,
|
||||
/* .MaxVertexAttribs = */ 64,
|
||||
/* .MaxVertexUniformComponents = */ 4096,
|
||||
/* .MaxVaryingFloats = */ 64,
|
||||
/* .MaxVertexTextureImageUnits = */ 0,
|
||||
/* .MaxCombinedTextureImageUnits = */ 0,
|
||||
/* .MaxTextureImageUnits = */ 0,
|
||||
/* .MaxFragmentUniformComponents = */ 0,
|
||||
/* .MaxDrawBuffers = */ 0,
|
||||
/* .MaxVertexUniformVectors = */ 128,
|
||||
/* .MaxVaryingVectors = */ 8,
|
||||
/* .MaxFragmentUniformVectors = */ 0,
|
||||
/* .MaxVertexOutputVectors = */ 16,
|
||||
/* .MaxFragmentInputVectors = */ 0,
|
||||
/* .MinProgramTexelOffset = */ -8,
|
||||
/* .MaxProgramTexelOffset = */ 7,
|
||||
/* .MaxClipDistances = */ 8,
|
||||
/* .MaxComputeWorkGroupCountX = */ 65535,
|
||||
/* .MaxComputeWorkGroupCountY = */ 65535,
|
||||
/* .MaxComputeWorkGroupCountZ = */ 65535,
|
||||
/* .MaxComputeWorkGroupSizeX = */ 1024,
|
||||
/* .MaxComputeWorkGroupSizeY = */ 1024,
|
||||
/* .MaxComputeWorkGroupSizeZ = */ 64,
|
||||
/* .MaxComputeUniformComponents = */ 1024,
|
||||
/* .MaxComputeTextureImageUnits = */ 16,
|
||||
/* .MaxComputeImageUniforms = */ 8,
|
||||
/* .MaxComputeAtomicCounters = */ 8,
|
||||
/* .MaxComputeAtomicCounterBuffers = */ 1,
|
||||
/* .MaxVaryingComponents = */ 60,
|
||||
/* .MaxVertexOutputComponents = */ 64,
|
||||
/* .MaxGeometryInputComponents = */ 64,
|
||||
/* .MaxGeometryOutputComponents = */ 128,
|
||||
/* .MaxFragmentInputComponents = */ 0,
|
||||
/* .MaxImageUnits = */ 0,
|
||||
/* .MaxCombinedImageUnitsAndFragmentOutputs = */ 0,
|
||||
/* .MaxCombinedShaderOutputResources = */ 8,
|
||||
/* .MaxImageSamples = */ 0,
|
||||
/* .MaxVertexImageUniforms = */ 0,
|
||||
/* .MaxTessControlImageUniforms = */ 0,
|
||||
/* .MaxTessEvaluationImageUniforms = */ 0,
|
||||
/* .MaxGeometryImageUniforms = */ 0,
|
||||
/* .MaxFragmentImageUniforms = */ 0,
|
||||
/* .MaxCombinedImageUniforms = */ 0,
|
||||
/* .MaxGeometryTextureImageUnits = */ 0,
|
||||
/* .MaxGeometryOutputVertices = */ 256,
|
||||
/* .MaxGeometryTotalOutputComponents = */ 1024,
|
||||
/* .MaxGeometryUniformComponents = */ 1024,
|
||||
/* .MaxGeometryVaryingComponents = */ 64,
|
||||
/* .MaxTessControlInputComponents = */ 128,
|
||||
/* .MaxTessControlOutputComponents = */ 128,
|
||||
/* .MaxTessControlTextureImageUnits = */ 0,
|
||||
/* .MaxTessControlUniformComponents = */ 1024,
|
||||
/* .MaxTessControlTotalOutputComponents = */ 4096,
|
||||
/* .MaxTessEvaluationInputComponents = */ 128,
|
||||
/* .MaxTessEvaluationOutputComponents = */ 128,
|
||||
/* .MaxTessEvaluationTextureImageUnits = */ 16,
|
||||
/* .MaxTessEvaluationUniformComponents = */ 1024,
|
||||
/* .MaxTessPatchComponents = */ 120,
|
||||
/* .MaxPatchVertices = */ 32,
|
||||
/* .MaxTessGenLevel = */ 64,
|
||||
/* .MaxViewports = */ 16,
|
||||
/* .MaxVertexAtomicCounters = */ 0,
|
||||
/* .MaxTessControlAtomicCounters = */ 0,
|
||||
/* .MaxTessEvaluationAtomicCounters = */ 0,
|
||||
/* .MaxGeometryAtomicCounters = */ 0,
|
||||
/* .MaxFragmentAtomicCounters = */ 0,
|
||||
/* .MaxCombinedAtomicCounters = */ 8,
|
||||
/* .MaxAtomicCounterBindings = */ 1,
|
||||
/* .MaxVertexAtomicCounterBuffers = */ 0,
|
||||
/* .MaxTessControlAtomicCounterBuffers = */ 0,
|
||||
/* .MaxTessEvaluationAtomicCounterBuffers = */ 0,
|
||||
/* .MaxGeometryAtomicCounterBuffers = */ 0,
|
||||
/* .MaxFragmentAtomicCounterBuffers = */ 0,
|
||||
/* .MaxCombinedAtomicCounterBuffers = */ 1,
|
||||
/* .MaxAtomicCounterBufferSize = */ 16384,
|
||||
/* .MaxTransformFeedbackBuffers = */ 4,
|
||||
/* .MaxTransformFeedbackInterleavedComponents = */ 64,
|
||||
/* .MaxCullDistances = */ 8,
|
||||
/* .MaxCombinedClipAndCullDistances = */ 8,
|
||||
/* .MaxSamples = */ 4,
|
||||
/* .maxMeshOutputVerticesNV = */ 256,
|
||||
/* .maxMeshOutputPrimitivesNV = */ 512,
|
||||
/* .maxMeshWorkGroupSizeX_NV = */ 32,
|
||||
/* .maxMeshWorkGroupSizeY_NV = */ 1,
|
||||
/* .maxMeshWorkGroupSizeZ_NV = */ 1,
|
||||
/* .maxTaskWorkGroupSizeX_NV = */ 32,
|
||||
/* .maxTaskWorkGroupSizeY_NV = */ 1,
|
||||
/* .maxTaskWorkGroupSizeZ_NV = */ 1,
|
||||
/* .maxMeshViewCountNV = */ 4,
|
||||
/* .maxDualSourceDrawBuffersEXT = */ 1,
|
||||
|
||||
/* .limits = */
|
||||
{
|
||||
/* .nonInductiveForLoops = */ 1,
|
||||
/* .whileLoops = */ 1,
|
||||
/* .doWhileLoops = */ 1,
|
||||
/* .generalUniformIndexing = */ 1,
|
||||
/* .generalAttributeMatrixVectorIndexing = */ 1,
|
||||
/* .generalVaryingIndexing = */ 1,
|
||||
/* .generalSamplerIndexing = */ 1,
|
||||
/* .generalVariableIndexing = */ 1,
|
||||
/* .generalConstantMatrixVectorIndexing = */ 1,
|
||||
}
|
||||
};
|
||||
|
||||
/**
|
||||
Shader utily class with functions to compile and process glsl files.
|
||||
*/
|
||||
class Shader
|
||||
{
|
||||
public:
|
||||
|
||||
// The default resource limit for the GLSL compiler, can be overwritten
|
||||
// Has been adopted by:
|
||||
// https://github.com/KhronosGroup/glslang/blob/master/StandAlone/ResourceLimits.cpp
|
||||
const static TBuiltInResource defaultResource;
|
||||
|
||||
/**
|
||||
* Compile multiple sources with optional filenames. Currently this function
|
||||
* uses the glslang C++ interface which is not thread safe so this funciton
|
||||
|
|
@ -873,7 +767,7 @@ class Shader
|
|||
const std::vector<std::string>& files = {},
|
||||
const std::string& entryPoint = "main",
|
||||
std::vector<std::pair<std::string, std::string>> definitions = {},
|
||||
const TBuiltInResource& resources = defaultResource);
|
||||
const TBuiltInResource& resources = Shader::defaultResource);
|
||||
|
||||
/**
|
||||
* Compile a single glslang source from string value. Currently this
|
||||
|
|
@ -893,7 +787,7 @@ class Shader
|
|||
const std::string& source,
|
||||
const std::string& entryPoint = "main",
|
||||
std::vector<std::pair<std::string, std::string>> definitions = {},
|
||||
const TBuiltInResource& resources = defaultResource);
|
||||
const TBuiltInResource& resources = Shader::defaultResource);
|
||||
};
|
||||
|
||||
}
|
||||
|
|
@ -1125,11 +1019,19 @@ class Algorithm
|
|||
{
|
||||
public:
|
||||
/**
|
||||
* Default constructor for Algorithm
|
||||
* Main constructor for algorithm with configuration parameters to create
|
||||
* the underlying resources.
|
||||
*
|
||||
* @param device The Vulkan device to use for creating resources
|
||||
* @param commandBuffer The vulkan command buffer to bind the pipeline and
|
||||
* shaders
|
||||
* @param tensors (optional) The tensors to use to create the descriptor resources
|
||||
* @param spirv (optional) The spirv code to use to create the algorithm
|
||||
* @param workgroup (optional) The kp::Workgroup to use for the dispatch which defaults to
|
||||
* kp::Workgroup(tensor[0].size(), 1, 1) if not set.
|
||||
* @param specializationConstants (optional) The kp::Constants to use to initialize
|
||||
* the specialization constants which cannot be changed once set.
|
||||
* @param pushConstants (optional) The kp::Constants to use when initializing the
|
||||
* pipeline, which set the size of the push constants - these can be modified but
|
||||
* all new values must have the same vector size as this initial value.
|
||||
*/
|
||||
Algorithm(std::shared_ptr<vk::Device> device,
|
||||
const std::vector<std::shared_ptr<Tensor>>& tensors = {},
|
||||
|
|
@ -1139,13 +1041,18 @@ class Algorithm
|
|||
const Constants& pushConstants = {});
|
||||
|
||||
/**
|
||||
* Initialiser for the shader data provided to the algorithm as well as
|
||||
* tensor parameters that will be used in shader.
|
||||
* Rebuild function to reconstruct algorithm with configuration parameters to create
|
||||
* the underlying resources.
|
||||
*
|
||||
* @param shaderFileData The bytes in spir-v format of the shader
|
||||
* @tensorParams The Tensors to be used in the Algorithm / shader for
|
||||
* @specalizationInstalces The specialization parameters to pass to the
|
||||
* function processing
|
||||
* @param tensors The tensors to use to create the descriptor resources
|
||||
* @param spirv The spirv code to use to create the algorithm
|
||||
* @param workgroup (optional) The kp::Workgroup to use for the dispatch which defaults to
|
||||
* kp::Workgroup(tensor[0].size(), 1, 1) if not set.
|
||||
* @param specializationConstants (optional) The kp::Constants to use to initialize
|
||||
* the specialization constants which cannot be changed once set.
|
||||
* @param pushConstants (optional) The kp::Constants to use when initializing the
|
||||
* pipeline, which set the size of the push constants - these can be modified but
|
||||
* all new values must have the same vector size as this initial value.
|
||||
*/
|
||||
void rebuild(const std::vector<std::shared_ptr<Tensor>>& tensors,
|
||||
const std::vector<uint32_t>& spirv,
|
||||
|
|
@ -1163,24 +1070,77 @@ class Algorithm
|
|||
* Records the dispatch function with the provided template parameters or
|
||||
* alternatively using the size of the tensor by default.
|
||||
*
|
||||
* @param x Layout X dispatch value
|
||||
* @param y Layout Y dispatch value
|
||||
* @param z Layout Z dispatch value
|
||||
* @param commandBuffer Command buffer to record the algorithm resources to
|
||||
*/
|
||||
void recordDispatch(const vk::CommandBuffer& commandBuffer);
|
||||
|
||||
void bindCore(const vk::CommandBuffer& commandBuffer);
|
||||
/**
|
||||
* Records command that binds the "core" algorithm components which consist of
|
||||
* binding the pipeline and binding the descriptorsets.
|
||||
*
|
||||
* @param commandBuffer Command buffer to record the algorithm resources to
|
||||
*/
|
||||
void recordBindCore(const vk::CommandBuffer& commandBuffer);
|
||||
|
||||
void bindPush(const vk::CommandBuffer& commandBuffer);
|
||||
/**
|
||||
* Records command that binds the push constants to the command buffer provided
|
||||
* - it is required that the pushConstants provided are of the same size as the
|
||||
* ones provided during initialization.
|
||||
*
|
||||
* @param commandBuffer Command buffer to record the algorithm resources to
|
||||
*/
|
||||
void recordBindPush(const vk::CommandBuffer& commandBuffer);
|
||||
|
||||
/**
|
||||
* function that checks all the gpu resource components to verify if these have
|
||||
* been created and returns true if all are valid.
|
||||
*
|
||||
* @returns returns true if the algorithm is currently initialized.
|
||||
*/
|
||||
bool isInit();
|
||||
|
||||
/**
|
||||
* Sets the work group to use in the recordDispatch
|
||||
*
|
||||
* @param workgroup The kp::Workgroup value to use to update the algorithm. It
|
||||
* must have a value greater than 1 on the x value (index 1) otherwise it will
|
||||
* be initialized on the size of the first tensor (ie. this->mTensor[0]->size())
|
||||
*/
|
||||
void setWorkgroup(const Workgroup& workgroup, uint32_t minSize = 1);
|
||||
/**
|
||||
* Sets the push constants to the new value provided to use in the next bindPush()
|
||||
*
|
||||
* @param The kp::Constant to use to set the push constants to use in the next
|
||||
* bindPush(...) calls. The constants provided must be of the same size as the
|
||||
* ones created during initialization.
|
||||
*/
|
||||
void setPush(const Constants& pushConstants);
|
||||
|
||||
/**
|
||||
* Gets the current workgroup from the algorithm.
|
||||
*
|
||||
* @param The kp::Constant to use to set the push constants to use in the next
|
||||
* bindPush(...) calls. The constants provided must be of the same size as the
|
||||
* ones created during initialization.
|
||||
*/
|
||||
const Workgroup& getWorkgroup();
|
||||
/**
|
||||
* Gets the specialization constants of the current algorithm.
|
||||
*
|
||||
* @returns The kp::Constants currently set for specialization constants
|
||||
*/
|
||||
const Constants& getSpecializationConstants();
|
||||
/**
|
||||
* Gets the specialization constants of the current algorithm.
|
||||
*
|
||||
* @returns The kp::Constants currently set for push constants
|
||||
*/
|
||||
const Constants& getPush();
|
||||
/**
|
||||
* Gets the current tensors that are used in the algorithm.
|
||||
*
|
||||
* @returns The list of tensors used in the algorithm.
|
||||
*/
|
||||
const std::vector<std::shared_ptr<Tensor>>& getTensors();
|
||||
|
||||
void destroy();
|
||||
|
|
@ -1212,8 +1172,6 @@ class Algorithm
|
|||
Constants mPushConstants;
|
||||
Workgroup mWorkgroup;
|
||||
|
||||
bool mIsInit;
|
||||
|
||||
// Create util functions
|
||||
void createShaderModule();
|
||||
void createPipeline();
|
||||
|
|
@ -1543,6 +1501,14 @@ class Sequence : public std::enable_shared_from_this<Sequence>
|
|||
~Sequence();
|
||||
|
||||
/**
|
||||
* Record function for operation to be added to the GPU queue in batch. This
|
||||
* template requires classes to be derived from the OpBase class. This
|
||||
* function also requires the Sequence to be recording, otherwise it will
|
||||
* not be able to add the operation.
|
||||
*
|
||||
* @param op Object derived from kp::BaseOp that will be recoreded by the sequence
|
||||
* which will be used when the operation is evaluated.
|
||||
* @return shared_ptr<Sequence> of the Sequence class itself
|
||||
*/
|
||||
std::shared_ptr<Sequence> record(std::shared_ptr<OpBase> op);
|
||||
|
||||
|
|
@ -1555,6 +1521,7 @@ class Sequence : public std::enable_shared_from_this<Sequence>
|
|||
* @param tensors Vector of tensors to use for the operation
|
||||
* @param TArgs Template parameters that are used to initialise operation
|
||||
* which allows for extensible configurations on initialisation.
|
||||
* @return shared_ptr<Sequence> of the Sequence class itself
|
||||
*/
|
||||
template<typename T, typename... TArgs>
|
||||
std::shared_ptr<Sequence> record(
|
||||
|
|
@ -1563,6 +1530,18 @@ class Sequence : public std::enable_shared_from_this<Sequence>
|
|||
std::shared_ptr<T> op{ new T(tensors, std::forward<TArgs>(params)...) };
|
||||
return this->record(op);
|
||||
}
|
||||
/**
|
||||
* Record function for operation to be added to the GPU queue in batch. This
|
||||
* template requires classes to be derived from the OpBase class. This
|
||||
* function also requires the Sequence to be recording, otherwise it will
|
||||
* not be able to add the operation.
|
||||
*
|
||||
* @param algorithm Algorithm to use for the record often used for OpAlgo
|
||||
* operations
|
||||
* @param TArgs Template parameters that are used to initialise operation
|
||||
* which allows for extensible configurations on initialisation.
|
||||
* @return shared_ptr<Sequence> of the Sequence class itself
|
||||
*/
|
||||
template<typename T, typename... TArgs>
|
||||
std::shared_ptr<Sequence> record(std::shared_ptr<Algorithm> algorithm,
|
||||
TArgs&&... params)
|
||||
|
|
@ -1574,21 +1553,29 @@ class Sequence : public std::enable_shared_from_this<Sequence>
|
|||
|
||||
/**
|
||||
* Eval sends all the recorded and stored operations in the vector of
|
||||
* operations into the gpu as a submit job with a barrier.
|
||||
* operations into the gpu as a submit job synchronously (with a barrier).
|
||||
*
|
||||
* @return shared_ptr<Sequence> of the Sequence class itself
|
||||
*/
|
||||
std::shared_ptr<Sequence> eval();
|
||||
|
||||
/**
|
||||
* Resets all the recorded and stored operations, records the operation
|
||||
* provided and submits into the gpu as a submit job synchronously (with a barrier).
|
||||
*
|
||||
* @return shared_ptr<Sequence> of the Sequence class itself
|
||||
*/
|
||||
std::shared_ptr<Sequence> eval(std::shared_ptr<OpBase> op);
|
||||
|
||||
/**
|
||||
* Eval sends all the recorded and stored operations in the vector of
|
||||
* operations into the gpu as a submit job with a barrier.
|
||||
*
|
||||
* @param tensors Vector of tensors to use for the operation
|
||||
* @param TArgs Template parameters that are used to initialise operation
|
||||
* which allows for extensible configurations on initialisation.
|
||||
* @return shared_ptr<Sequence> of the Sequence class itself
|
||||
*/
|
||||
// TODO: Aim to have only a single function with tensors/algorithm
|
||||
template<typename T, typename... TArgs>
|
||||
std::shared_ptr<Sequence> eval(std::vector<std::shared_ptr<Tensor>> tensors,
|
||||
TArgs&&... params)
|
||||
|
|
@ -1596,6 +1583,16 @@ class Sequence : public std::enable_shared_from_this<Sequence>
|
|||
std::shared_ptr<T> op{ new T(tensors, std::forward<TArgs>(params)...) };
|
||||
return this->eval(op);
|
||||
}
|
||||
/**
|
||||
* Eval sends all the recorded and stored operations in the vector of
|
||||
* operations into the gpu as a submit job with a barrier.
|
||||
*
|
||||
* @param algorithm Algorithm to use for the record often used for OpAlgo
|
||||
* operations
|
||||
* @param TArgs Template parameters that are used to initialise operation
|
||||
* which allows for extensible configurations on initialisation.
|
||||
* @return shared_ptr<Sequence> of the Sequence class itself
|
||||
*/
|
||||
template<typename T, typename... TArgs>
|
||||
std::shared_ptr<Sequence> eval(std::shared_ptr<Algorithm> algorithm,
|
||||
TArgs&&... params)
|
||||
|
|
@ -1607,18 +1604,27 @@ class Sequence : public std::enable_shared_from_this<Sequence>
|
|||
|
||||
/**
|
||||
* Eval Async sends all the recorded and stored operations in the vector of
|
||||
* operations into the gpu as a submit job with a barrier. EvalAwait() must
|
||||
* be called after to ensure the sequence is terminated correctly.
|
||||
* operations into the gpu as a submit job without a barrier. EvalAwait() must
|
||||
* ALWAYS be called after to ensure the sequence is terminated correctly.
|
||||
*
|
||||
* @return Boolean stating whether execution was successful.
|
||||
*/
|
||||
std::shared_ptr<Sequence> evalAsync();
|
||||
/**
|
||||
* Clears currnet operations to record provided one in the vector of
|
||||
* operations into the gpu as a submit job without a barrier. EvalAwait() must
|
||||
* ALWAYS be called after to ensure the sequence is terminated correctly.
|
||||
*
|
||||
* @return Boolean stating whether execution was successful.
|
||||
*/
|
||||
std::shared_ptr<Sequence> evalAsync(std::shared_ptr<OpBase> op);
|
||||
|
||||
/**
|
||||
* Eval sends all the recorded and stored operations in the vector of
|
||||
* operations into the gpu as a submit job with a barrier.
|
||||
*
|
||||
* @param tensors Vector of tensors to use for the operation
|
||||
* @param TArgs Template parameters that are used to initialise operation
|
||||
* which allows for extensible configurations on initialisation.
|
||||
* @return shared_ptr<Sequence> of the Sequence class itself
|
||||
*/
|
||||
template<typename T, typename... TArgs>
|
||||
|
|
@ -1629,6 +1635,16 @@ class Sequence : public std::enable_shared_from_this<Sequence>
|
|||
std::shared_ptr<T> op{ new T(tensors, std::forward<TArgs>(params)...) };
|
||||
return this->evalAsync(op);
|
||||
}
|
||||
/**
|
||||
* Eval sends all the recorded and stored operations in the vector of
|
||||
* operations into the gpu as a submit job with a barrier.
|
||||
*
|
||||
* @param algorithm Algorithm to use for the record often used for OpAlgo
|
||||
* operations
|
||||
* @param TArgs Template parameters that are used to initialise operation
|
||||
* which allows for extensible configurations on initialisation.
|
||||
* @return shared_ptr<Sequence> of the Sequence class itself
|
||||
*/
|
||||
template<typename T, typename... TArgs>
|
||||
std::shared_ptr<Sequence> evalAsync(std::shared_ptr<Algorithm> algorithm,
|
||||
TArgs&&... params)
|
||||
|
|
@ -1643,7 +1659,7 @@ class Sequence : public std::enable_shared_from_this<Sequence>
|
|||
* finishes, it runs the postEval of all operations.
|
||||
*
|
||||
* @param waitFor Number of milliseconds to wait before timing out.
|
||||
* @return Boolean stating whether execution was successful.
|
||||
* @return shared_ptr<Sequence> of the Sequence class itself
|
||||
*/
|
||||
std::shared_ptr<Sequence> evalAwait(uint64_t waitFor = UINT64_MAX);
|
||||
|
||||
|
|
@ -1676,8 +1692,19 @@ class Sequence : public std::enable_shared_from_this<Sequence>
|
|||
*/
|
||||
bool isRecording();
|
||||
|
||||
/**
|
||||
* Returns true if the sequence has been initialised, and it's based on the
|
||||
* GPU resources being refrenced.
|
||||
*
|
||||
* @return Boolean stating if is initialized
|
||||
*/
|
||||
bool isInit();
|
||||
|
||||
/**
|
||||
* Clears command buffer and triggers re-record of all the current operations
|
||||
* saved, which is useful if the underlying kp::Tensors or kp::Algorithms
|
||||
* are modified and need to be re-recorded.
|
||||
*/
|
||||
void rerecord();
|
||||
|
||||
/**
|
||||
|
|
@ -1742,15 +1769,13 @@ class Manager
|
|||
Manager();
|
||||
|
||||
/**
|
||||
* Similar to base constructor but allows the user to provide the device
|
||||
* they would like to create the resources on.
|
||||
* Similar to base constructor but allows for further configuration to use when
|
||||
* creating the Vulkan resources.
|
||||
*
|
||||
* @param physicalDeviceIndex The index of the physical device to use
|
||||
* @param manageResources (Optional) Whether to manage the memory of the
|
||||
* resources created and destroy when the manager is destroyed.
|
||||
* @param familyQueueIndices (Optional) List of queue indices to add for
|
||||
* explicit allocation
|
||||
* @param totalQueues The total number of compute queues to create.
|
||||
* @param desiredExtensions The desired extensions to load from physicalDevice
|
||||
*/
|
||||
Manager(uint32_t physicalDeviceIndex,
|
||||
const std::vector<uint32_t>& familyQueueIndices = {},
|
||||
|
|
@ -1776,32 +1801,40 @@ class Manager
|
|||
~Manager();
|
||||
|
||||
/**
|
||||
* Get or create a managed Sequence that will be contained by this manager.
|
||||
* If the named sequence does not currently exist, it would be created and
|
||||
* initialised.
|
||||
* Create a managed sequence that will be destroyed by this manager
|
||||
* if it hasn't been destroyed by its reference count going to zero.
|
||||
*
|
||||
* @param sequenceName The name for the named sequence to be retrieved or
|
||||
* created
|
||||
* @param queueIndex The queue to use from the available queues
|
||||
* @return Shared pointer to the manager owned sequence resource
|
||||
* @returns Shared pointer with initialised sequence
|
||||
*/
|
||||
std::shared_ptr<Sequence> sequence(uint32_t queueIndex = 0);
|
||||
|
||||
/**
|
||||
* Function that simplifies the common workflow of tensor creation and
|
||||
* initialization. It will take the constructor parameters for a Tensor
|
||||
* and will will us it to create a new Tensor and then create it. The
|
||||
* tensor memory will then be managed and owned by the manager.
|
||||
* Create a managed tensor that will be destroyed by this manager
|
||||
* if it hasn't been destroyed by its reference count going to zero.
|
||||
*
|
||||
* @param data The data to initialize the tensor with
|
||||
* @param tensorType The type of tensor to initialize
|
||||
* @param syncDataToGPU Whether to sync the data to GPU memory
|
||||
* @returns Initialized Tensor with memory Syncd to GPU device
|
||||
* @returns Shared pointer with initialised tensor
|
||||
*/
|
||||
std::shared_ptr<Tensor> tensor(
|
||||
const std::vector<float>& data,
|
||||
Tensor::TensorTypes tensorType = Tensor::TensorTypes::eDevice);
|
||||
|
||||
/**
|
||||
* Create a managed algorithm that will be destroyed by this manager
|
||||
* if it hasn't been destroyed by its reference count going to zero.
|
||||
*
|
||||
* @param tensors (optional) The tensors to initialise the algorithm with
|
||||
* @param spirv (optional) The SPIRV bytes for the algorithm to dispatch
|
||||
* @param workgroup (optional) kp::Workgroup for algorithm to use, and
|
||||
* defaults to (tensor[0].size(), 1, 1)
|
||||
* @param specializationConstants (optional) kp::Constant to use for
|
||||
* specialization constants, and defaults to an empty constant
|
||||
* @param pushConstants (optional) kp::Constant to use for push constants,
|
||||
* and defaults to an empty constant
|
||||
* @returns Shared pointer with initialised algorithm
|
||||
*/
|
||||
std::shared_ptr<Algorithm> algorithm(
|
||||
const std::vector<std::shared_ptr<Tensor>>& tensors = {},
|
||||
const std::vector<uint32_t>& spirv = {},
|
||||
|
|
@ -1809,7 +1842,14 @@ class Manager
|
|||
const Constants& specializationConstants = {},
|
||||
const Constants& pushConstants = {});
|
||||
|
||||
/**
|
||||
* Destroy the GPU resources and all managed resources by manager.
|
||||
**/
|
||||
void destroy();
|
||||
/**
|
||||
* Run a pseudo-garbage collection to release all the managed resources
|
||||
* that have been already freed due to these reaching to zero ref count.
|
||||
**/
|
||||
void clear();
|
||||
|
||||
private:
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue