diff options
Diffstat (limited to 'src/runtime/CL/functions/CLFullyConnectedLayer.cpp')
-rw-r--r-- | src/runtime/CL/functions/CLFullyConnectedLayer.cpp | 34 |
1 files changed, 16 insertions, 18 deletions
diff --git a/src/runtime/CL/functions/CLFullyConnectedLayer.cpp b/src/runtime/CL/functions/CLFullyConnectedLayer.cpp index 6fd78a3fc9..60c28a0874 100644 --- a/src/runtime/CL/functions/CLFullyConnectedLayer.cpp +++ b/src/runtime/CL/functions/CLFullyConnectedLayer.cpp @@ -73,12 +73,11 @@ Status CLFullyConnectedLayerReshapeWeights::validate(const ITensorInfo *input, c } CLFullyConnectedLayer::CLFullyConnectedLayer(std::shared_ptr<IMemoryManager> memory_manager) - : _memory_group(memory_manager), _im2col_kernel(), _convert_weights(), _reshape_weights_kernel(), _mm_gemm(memory_manager), _mm_gemmlowp(memory_manager), _gemmlowp_output_stage(), - _accumulate_biases_kernel(), _im2col_output(), _gemmlowp_output(), _converted_weights_output(), _reshape_weights_output(), _are_weights_converted(true), _are_weights_reshaped(true), + : _memory_group(memory_manager), _convert_weights(), _flatten_layer(), _reshape_weights_kernel(), _mm_gemm(memory_manager), _mm_gemmlowp(memory_manager), _gemmlowp_output_stage(), + _accumulate_biases_kernel(), _flatten_output(), _gemmlowp_output(), _converted_weights_output(), _reshape_weights_output(), _are_weights_converted(true), _are_weights_reshaped(true), _is_fc_after_conv(true), _accumulate_biases(false), _is_quantized(false), _is_prepared(false), _original_weights(nullptr) { } - void CLFullyConnectedLayer::configure_mm(const ICLTensor *input, const ICLTensor *weights, ICLTensor *output) { if(_is_quantized) @@ -111,20 +110,19 @@ void CLFullyConnectedLayer::configure_conv_fc(const ICLTensor *input, const ICLT // If the fully connected layer is called after a convolution layer, the input tensor must be linearized - // Initialize output tensor for im2col - TensorShape shape_im2col = compute_im2col_fc_shape(input->info()); - _im2col_output.allocator()->init(input->info()->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(shape_im2col).set_data_layout(DataLayout::NCHW)); + // Initialize output tensor for flatten + TensorShape shape_flatten = compute_flatten_shape(input->info()); + _flatten_output.allocator()->init(input->info()->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(shape_flatten).set_data_layout(DataLayout::NCHW)); - // Configure im2col kernel - _memory_group.manage(&_im2col_output); - _im2col_kernel.configure(input, &_im2col_output, Size2D(1, 1), PadStrideInfo(1, 1, 0, 0), false); - CLScheduler::get().tune_kernel_static(_im2col_kernel); + // Configure flatten kernel + _memory_group.manage(&_flatten_output); + _flatten_layer.configure(input, &_flatten_output); // Configure matrix multiply kernel - configure_mm(&_im2col_output, weights, output); + configure_mm(&_flatten_output, weights, output); - // Allocate the output tensor for im2col once all the configure methods have been called - _im2col_output.allocator()->allocate(); + // Allocate the output tensor for flatten once all the configure methods have been called + _flatten_output.allocator()->allocate(); } void CLFullyConnectedLayer::configure_fc_fc(const ICLTensor *input, const ICLTensor *weights, ICLTensor *output) @@ -254,7 +252,7 @@ Status CLFullyConnectedLayer::validate(const ITensorInfo *input, const ITensorIn bool is_quantized = is_data_type_quantized_asymmetric(input->data_type()); const GPUTarget gpu_target = CLScheduler::get().target(); - const ITensorInfo &im2col_input = TensorInfo(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(compute_im2col_fc_shape(input)).set_data_layout(DataLayout::NCHW)); + const ITensorInfo &flatten_input = TensorInfo(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(compute_flatten_shape(input)).set_data_layout(DataLayout::NCHW)); const ITensorInfo &reshaped_weights = TensorInfo(weights->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(compute_transposed_shape(*weights))); const ITensorInfo &converted_weights = weights_reshaped ? TensorInfo(weights->clone()->set_is_resizable(true).reset_padding()) : TensorInfo(*reshaped_weights.clone()); const ITensorInfo &gemmlowp_output = TensorInfo(output->clone()->set_is_resizable(true).reset_padding().set_data_type(DataType::S32)); @@ -311,9 +309,9 @@ Status CLFullyConnectedLayer::validate(const ITensorInfo *input, const ITensorIn // Fully Connected layer after a Convolution Layer without batches ARM_COMPUTE_RETURN_ERROR_ON((weights_to_use->dimension(1) != (input->dimension(0) * input->dimension(1) * input->dimension(2)))); - // Validate im2col kernel - ARM_COMPUTE_RETURN_ON_ERROR(CLIm2ColKernel::validate(input, &im2col_input, Size2D(1, 1), PadStrideInfo(1, 1, 0, 0), false)); - input_to_use = &im2col_input; + // Validate flatten kernel + ARM_COMPUTE_RETURN_ON_ERROR(CLFlattenLayer::validate(input, &flatten_input)); + input_to_use = &flatten_input; } else { @@ -341,7 +339,7 @@ void CLFullyConnectedLayer::run() // Linearize input if it comes from a convolutional layer if(_is_fc_after_conv) { - CLScheduler::get().enqueue(_im2col_kernel, false); + _flatten_layer.run(); } // Run matrix multiply |