Add tensor related data structures for the new API
Adds the following:
- TensorDescriptor: which is responsible for holding the information
needed to represent a tensor (e.g. shape, dimensions, etc)
- Tensor: an aggreate object of a descriptor and a backing memory
- TensorPack: A map of tensor that can be passed to operators as
inputs/outputs
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: I02734ac6ad85700d91d6e73217b4637adbf5d177
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5260
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/gpu/cl/ClTensor.cpp b/src/gpu/cl/ClTensor.cpp
new file mode 100644
index 0000000..db2081c
--- /dev/null
+++ b/src/gpu/cl/ClTensor.cpp
@@ -0,0 +1,92 @@
+/*
+ * Copyright (c) 2021 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/gpu/cl/ClTensor.h"
+
+#include "src/common/utils/LegacySupport.h"
+
+namespace arm_compute
+{
+namespace gpu
+{
+namespace opencl
+{
+ClTensor::ClTensor(IContext *ctx, const AclTensorDescriptor &desc)
+ : ITensorV2(ctx), _legacy_tensor()
+{
+ ARM_COMPUTE_ASSERT((ctx != nullptr) && (ctx->type() == Target::GpuOcl));
+ _legacy_tensor = std::make_unique<CLTensor>();
+ _legacy_tensor->allocator()->init(arm_compute::detail::convert_to_legacy_tensor_info(desc));
+}
+
+void *ClTensor::map()
+{
+ ARM_COMPUTE_ASSERT(_legacy_tensor.get() != nullptr);
+
+ if(_legacy_tensor == nullptr)
+ {
+ ARM_COMPUTE_LOG_ERROR_ACL("[ClTensor:map]: Backing tensor does not exist!");
+ return nullptr;
+ }
+
+ _legacy_tensor->map();
+ return _legacy_tensor->buffer();
+}
+
+StatusCode ClTensor::unmap()
+{
+ ARM_COMPUTE_ASSERT(_legacy_tensor.get() != nullptr);
+
+ if(_legacy_tensor == nullptr)
+ {
+ ARM_COMPUTE_LOG_ERROR_ACL("[ClTensor:unmap]: Backing tensor does not exist!");
+ return StatusCode::RuntimeError;
+ }
+ _legacy_tensor->unmap();
+
+ return StatusCode::Success;
+}
+
+StatusCode ClTensor::allocate()
+{
+ ARM_COMPUTE_ASSERT(_legacy_tensor.get() != nullptr);
+
+ _legacy_tensor->allocator()->allocate();
+ return StatusCode::Success;
+}
+
+StatusCode ClTensor::import(void *handle, ImportMemoryType type)
+{
+ ARM_COMPUTE_ASSERT(_legacy_tensor.get() != nullptr);
+ ARM_COMPUTE_UNUSED(type, handle);
+
+ return StatusCode::Success;
+}
+
+arm_compute::ITensor *ClTensor::tensor()
+{
+ return _legacy_tensor.get();
+}
+} // namespace opencl
+} // namespace gpu
+} // namespace arm_compute