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Diffstat (limited to 'src/runtime/CL/functions/CLRNNLayer.cpp')
-rw-r--r--src/runtime/CL/functions/CLRNNLayer.cpp83
1 files changed, 60 insertions, 23 deletions
diff --git a/src/runtime/CL/functions/CLRNNLayer.cpp b/src/runtime/CL/functions/CLRNNLayer.cpp
index 57b8d70089..34b78eefa7 100644
--- a/src/runtime/CL/functions/CLRNNLayer.cpp
+++ b/src/runtime/CL/functions/CLRNNLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2020 ARM Limited.
+ * Copyright (c) 2018-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -29,23 +29,44 @@
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
-#include <utility>
+#include "src/common/utils/Log.h"
+#include "src/core/CL/kernels/CLFillBorderKernel.h"
-using namespace arm_compute;
+namespace arm_compute
+{
using namespace arm_compute::misc::shape_calculator;
CLRNNLayer::CLRNNLayer(std::shared_ptr<IMemoryManager> memory_manager)
- : _memory_group(std::move(memory_manager)), _gemm_state_f(), _add_kernel(), _activation_kernel(), _fully_connected_kernel(), _copy_kernel(), _fully_connected_out(), _gemm_output(), _add_output(),
+ : _memory_group(std::move(memory_manager)),
+ _gemm_state_f(),
+ _add_kernel(),
+ _activation(),
+ _fully_connected_kernel(),
+ _copy(),
+ _fully_connected_out(),
+ _gemm_output(),
+ _add_output(),
_is_prepared(false)
{
}
-Status CLRNNLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *recurrent_weights, const ITensorInfo *bias, const ITensorInfo *hidden_state,
- const ITensorInfo *output, const ActivationLayerInfo &info)
+CLRNNLayer::~CLRNNLayer() = default;
+
+Status CLRNNLayer::validate(const ITensorInfo *input,
+ const ITensorInfo *weights,
+ const ITensorInfo *recurrent_weights,
+ const ITensorInfo *bias,
+ const ITensorInfo *hidden_state,
+ const ITensorInfo *output,
+ const ActivationLayerInfo &info)
{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, recurrent_weights, bias, hidden_state, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights, recurrent_weights, bias, hidden_state, output);
+
const int idx_width = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::WIDTH);
const int idx_height = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::HEIGHT);
- ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, recurrent_weights, bias, hidden_state, output);
+
ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(idx_width) != weights->dimension(idx_width));
ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_height) != recurrent_weights->dimension(idx_width));
ARM_COMPUTE_RETURN_ERROR_ON(recurrent_weights->dimension(idx_width) != recurrent_weights->dimension(1));
@@ -55,28 +76,43 @@ Status CLRNNLayer::validate(const ITensorInfo *input, const ITensorInfo *weights
ARM_COMPUTE_RETURN_ERROR_ON(hidden_state->dimension(idx_height) != input->dimension(idx_height));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), hidden_state->tensor_shape());
- auto shape_info = TensorInfo(compute_rnn_shape(recurrent_weights, hidden_state->dimension(idx_height)), 1, input->data_type());
+ auto shape_info =
+ TensorInfo(compute_rnn_shape(recurrent_weights, hidden_state->dimension(idx_height)), 1, input->data_type());
ARM_COMPUTE_RETURN_ON_ERROR(CLFullyConnectedLayer::validate(input, weights, bias, &shape_info));
ARM_COMPUTE_RETURN_ON_ERROR(CLGEMM::validate(hidden_state, recurrent_weights, nullptr, &shape_info, 1.f, 0.f));
- ARM_COMPUTE_RETURN_ON_ERROR(CLSaturatedArithmeticOperationKernel::validate(ArithmeticOperation::ADD, &shape_info, &shape_info, &shape_info, ConvertPolicy::SATURATE));
- ARM_COMPUTE_RETURN_ON_ERROR(CLActivationLayerKernel::validate(&shape_info, &shape_info, info));
+ ARM_COMPUTE_RETURN_ON_ERROR(
+ CLArithmeticAddition::validate(&shape_info, &shape_info, &shape_info, ConvertPolicy::SATURATE));
+ ARM_COMPUTE_RETURN_ON_ERROR(CLActivationLayer::validate(&shape_info, &shape_info, info));
return Status{};
}
-void CLRNNLayer::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *recurrent_weights, const ICLTensor *bias, ICLTensor *hidden_state, ICLTensor *output,
+void CLRNNLayer::configure(const ICLTensor *input,
+ const ICLTensor *weights,
+ const ICLTensor *recurrent_weights,
+ const ICLTensor *bias,
+ ICLTensor *hidden_state,
+ ICLTensor *output,
ActivationLayerInfo &info)
{
- configure(CLKernelLibrary::get().get_compile_context(), input, weights, recurrent_weights, bias, hidden_state, output, info);
+ configure(CLKernelLibrary::get().get_compile_context(), input, weights, recurrent_weights, bias, hidden_state,
+ output, info);
}
-void CLRNNLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *recurrent_weights, const ICLTensor *bias,
- ICLTensor *hidden_state,
- ICLTensor *output, ActivationLayerInfo &info)
+void CLRNNLayer::configure(const CLCompileContext &compile_context,
+ const ICLTensor *input,
+ const ICLTensor *weights,
+ const ICLTensor *recurrent_weights,
+ const ICLTensor *bias,
+ ICLTensor *hidden_state,
+ ICLTensor *output,
+ ActivationLayerInfo &info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, recurrent_weights, bias, hidden_state, output);
- ARM_COMPUTE_ERROR_THROW_ON(CLRNNLayer::validate(input->info(), weights->info(), recurrent_weights->info(), bias->info(), hidden_state->info(), output->info(), info));
+ ARM_COMPUTE_ERROR_THROW_ON(CLRNNLayer::validate(input->info(), weights->info(), recurrent_weights->info(),
+ bias->info(), hidden_state->info(), output->info(), info));
+ ARM_COMPUTE_LOG_PARAMS(input, weights, recurrent_weights, bias, hidden_state, output, info);
const int idx_height = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT);
TensorShape shape = compute_rnn_shape(recurrent_weights->info(), hidden_state->info()->dimension(idx_height));
@@ -96,15 +132,15 @@ void CLRNNLayer::configure(const CLCompileContext &compile_context, const ICLTen
_add_output.allocator()->init(TensorInfo(shape, 1, input->info()->data_type()));
_memory_group.manage(&_add_output);
- _add_kernel.configure(compile_context, ArithmeticOperation::ADD, &_fully_connected_out, &_gemm_output, &_add_output, ConvertPolicy::SATURATE);
+ _add_kernel.configure(compile_context, &_fully_connected_out, &_gemm_output, &_add_output, ConvertPolicy::SATURATE);
_fully_connected_out.allocator()->allocate();
_gemm_output.allocator()->allocate();
- _activation_kernel.configure(compile_context, &_add_output, hidden_state, info);
+ _activation.configure(compile_context, &_add_output, hidden_state, info);
_add_output.allocator()->allocate();
- _copy_kernel.configure(compile_context, hidden_state, output);
+ _copy.configure(compile_context, hidden_state, output);
}
void CLRNNLayer::run()
@@ -115,16 +151,16 @@ void CLRNNLayer::run()
_fully_connected_kernel.run();
_gemm_state_f.run();
- CLScheduler::get().enqueue(_add_kernel);
- CLScheduler::get().enqueue(_activation_kernel);
+ _add_kernel.run();
+ _activation.run();
// copy hidden out to output
- CLScheduler::get().enqueue(_copy_kernel);
+ _copy.run();
}
void CLRNNLayer::prepare()
{
- if(!_is_prepared)
+ if (!_is_prepared)
{
_fully_connected_kernel.prepare();
_gemm_state_f.prepare();
@@ -132,3 +168,4 @@ void CLRNNLayer::prepare()
_is_prepared = true;
}
}
+} // namespace arm_compute
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-05 15:22:47 +0000