Integrate CLTensorArgument
- Add CLTensorArgument to query the components and storages as OpenCL
variables (or by values when possible)
- Add caching mechanism in CLTensorArgument to keep track of the components and storages used
- Add unit tests
Resolves COMPMID-5787
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Change-Id: Ib39e1f77b097e5b907a296fe6b0d41bb4bcd4ffc
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9908
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
diff --git a/compute_kernel_writer/src/cl/CLTensorArgument.cpp b/compute_kernel_writer/src/cl/CLTensorArgument.cpp
new file mode 100644
index 0000000..ed1c5bd
--- /dev/null
+++ b/compute_kernel_writer/src/cl/CLTensorArgument.cpp
@@ -0,0 +1,247 @@
+/*
+ * Copyright (c) 2023 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+
+#include "src/cl/CLTensorArgument.h"
+#include "ckw/Error.h"
+#include "src/cl/CLHelpers.h"
+#include "src/types/TensorComponentType.h"
+
+#include <algorithm>
+#include <vector>
+
+namespace ckw
+{
+CLTensorArgument::CLTensorArgument(const std::string &name, const TensorInfo &info, bool return_dims_by_value)
+{
+ _return_dims_by_value = return_dims_by_value;
+ _basename = name;
+ _info = info;
+}
+
+TileVariable CLTensorArgument::component(TensorComponentType x)
+{
+ if(_return_dims_by_value)
+ {
+ uint32_t component_type = static_cast<uint32_t>(x);
+
+ const bool is_dimension = (component_type & static_cast<uint32_t>(TensorComponentBitmask::Dimension)) != 0;
+ const bool is_folded_dimensions = (component_type & static_cast<uint32_t>(TensorComponentBitmask::FoldedDimensions)) != 0;
+
+ constexpr auto bitmask_all = static_cast<uint32_t>(TensorComponentIndexBitmask::All);
+ constexpr auto bitmask_index_0 = static_cast<uint32_t>(TensorComponentIndexBitmask::Index0);
+#ifdef COMPUTE_KERNEL_WRITER_ASSERTS_ENABLED
+ constexpr auto bitmask_index_1 = static_cast<uint32_t>(TensorComponentIndexBitmask::Index1);
+ constexpr auto bitmask_index_2 = static_cast<uint32_t>(TensorComponentIndexBitmask::Index2);
+ constexpr auto bitmask_index_3 = static_cast<uint32_t>(TensorComponentIndexBitmask::Index3);
+#endif // COMPUTE_KERNEL_WRITER_ASSERTS_ENABLED
+
+ // Make sure that the encoding of component type hasn't changed and each nibble is 4 bits apart.
+ CKW_ASSERT(bitmask_all == (bitmask_index_0 | bitmask_index_1 | bitmask_index_2 | bitmask_index_3));
+ CKW_ASSERT(bitmask_index_0 == bitmask_index_1 >> 4);
+ CKW_ASSERT(bitmask_index_1 == bitmask_index_2 >> 4);
+ CKW_ASSERT(bitmask_index_2 == bitmask_index_3 >> 4);
+
+ // If we have a dimension or folded dimensions, we can return the corresponding value if it is not dynamic (not equal to -1)
+ if(is_dimension == true || is_folded_dimensions == true)
+ {
+ component_type = component_type & bitmask_all;
+
+ int32_t idx = 1;
+ for(int32_t i = 0; i < tensor_component_index_max_count; ++i)
+ {
+ uint32_t dim_idx = component_type & bitmask_index_0;
+
+ if(dim_idx == 0)
+ {
+ // Stop at the first nibble containing 0
+ break;
+ }
+
+ // Subtract - 1. Please refer to the TensorComponentIndexBitmask documentation
+ dim_idx -= 1;
+
+ // Get the dimension value
+ const int32_t dim_val = _info.shape()[dim_idx];
+
+ if(dim_val == kDynamicTensorDimensionValue)
+ {
+ // We cannot return the dimension by value if it is dynamic.
+ // Therefore, force the idx variable to kDynamicTensorDimensionValue and break the loop.
+ idx = kDynamicTensorDimensionValue;
+ break;
+ }
+
+ idx *= dim_val;
+
+ // Go to the next nibble
+ component_type >>= 4;
+ }
+
+ if(idx != kDynamicTensorDimensionValue)
+ {
+ TileVariable t;
+ t.str = std::to_string(idx);
+ t.desc.dt = DataType::Uint32;
+ t.desc.len = 1;
+ return t;
+ }
+ }
+ }
+
+ auto it = std::find(_components_used.begin(), _components_used.end(), x);
+
+ // Add to the list of used components if not present yet
+ if(it == _components_used.end())
+ {
+ _components_used.push_back(x);
+ }
+
+ TileVariable t;
+ t.str = create_component_name(x);
+ t.desc.dt = DataType::Int32;
+ t.desc.len = 1;
+ return t;
+}
+
+TensorStorageVariable CLTensorArgument::storage(TensorStorageType x)
+{
+ if(std::find(_storages_used.begin(), _storages_used.end(), x) == _storages_used.end())
+ {
+ _storages_used.push_back(x);
+ }
+
+ TensorStorageVariable t;
+ t.val = create_storage_name(x);
+ t.type = cl_get_variable_storagetype_as_string(x);
+
+ return t;
+}
+
+std::string CLTensorArgument::create_storage_name(TensorStorageType x) const
+{
+ std::string var_name = _basename;
+
+ switch(x)
+ {
+ case TensorStorageType::BufferUint8Ptr:
+ var_name += "_ptr";
+ break;
+ case TensorStorageType::Texture2dReadOnly:
+ case TensorStorageType::Texture2dWriteOnly:
+ var_name += "_img2d";
+ break;
+ default:
+ CKW_ASSERT_FAILED_MSG("Unsupported tensor storage");
+ return "";
+ }
+
+ return var_name;
+}
+
+std::string CLTensorArgument::create_component_name(TensorComponentType x) const
+{
+ std::string var_name = _basename;
+
+ switch(x)
+ {
+ case TensorComponentType::OffsetFirstElement:
+ var_name += "_offset_first_element";
+ break;
+ case TensorComponentType::Stride0:
+ var_name += "_stride0";
+ break;
+ case TensorComponentType::Stride1:
+ var_name += "_stride1";
+ break;
+ case TensorComponentType::Stride2:
+ var_name += "_stride2";
+ break;
+ case TensorComponentType::Stride3:
+ var_name += "_stride3";
+ break;
+ case TensorComponentType::Stride4:
+ var_name += "_stride4";
+ break;
+ case TensorComponentType::Dim0:
+ var_name += "_dim0";
+ break;
+ case TensorComponentType::Dim1:
+ var_name += "_dim1";
+ break;
+ case TensorComponentType::Dim2:
+ var_name += "_dim2";
+ break;
+ case TensorComponentType::Dim3:
+ var_name += "_dim3";
+ break;
+ case TensorComponentType::Dim4:
+ var_name += "_dim4";
+ break;
+ case TensorComponentType::Dim1xDim2:
+ var_name += "_dim1xdim2";
+ break;
+ case TensorComponentType::Dim2xDim3:
+ var_name += "_dim2xdim3";
+ break;
+ case TensorComponentType::Dim1xDim2xDim3:
+ var_name += "_dim1xdim2xdim3";
+ break;
+ default:
+ COMPUTE_KERNEL_WRITER_ERROR_ON_MSG("Unsupported tensor component");
+ return "";
+ }
+
+ return var_name;
+}
+
+std::vector<TensorStorageVariable> CLTensorArgument::storages() const
+{
+ std::vector<TensorStorageVariable> storages;
+ for(auto &val : _storages_used)
+ {
+ TensorStorageVariable t;
+ t.val = create_storage_name(val);
+ t.type = cl_get_variable_storagetype_as_string(val);
+ storages.push_back(t);
+ }
+
+ return storages;
+}
+
+std::vector<TileVariable> CLTensorArgument::components() const
+{
+ std::vector<TileVariable> components;
+
+ for(auto &val : _components_used)
+ {
+ TileVariable t;
+ t.str = create_component_name(val);
+ t.desc.dt = DataType::Int32;
+ t.desc.len = 1;
+ components.push_back(t);
+ }
+
+ return components;
+}
+} // namespace ckw