diff options
Diffstat (limited to 'arm_compute/runtime/CL/functions/CLQLSTMLayer.h')
| -rw-r--r-- | arm_compute/runtime/CL/functions/CLQLSTMLayer.h | 102 |
1 files changed, 54 insertions, 48 deletions
diff --git a/arm_compute/runtime/CL/functions/CLQLSTMLayer.h b/arm_compute/runtime/CL/functions/CLQLSTMLayer.h index 722275e269..219f46ee48 100644 --- a/arm_compute/runtime/CL/functions/CLQLSTMLayer.h +++ b/arm_compute/runtime/CL/functions/CLQLSTMLayer.h @@ -24,6 +24,7 @@ #ifndef ARM_COMPUTE_CLQLSTMLAYER_H #define ARM_COMPUTE_CLQLSTMLAYER_H +#include "arm_compute/core/CL/kernels/CLCopyKernel.h" #include "arm_compute/core/CL/kernels/CLElementwiseOperationKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpReductionKernel.h" #include "arm_compute/core/CL/kernels/CLPixelWiseMultiplicationKernel.h" @@ -46,6 +47,7 @@ class ICLTensor; * This function calls the following CL functions/kernels: * * -# @ref CLActivationLayer Activation functions (tanh and logistic) + * -# @ref CLCopyKernel Copy kernel for copying output_state_out to output * -# @ref CLSaturatedArithmeticOperationKernel Elementwise addition and subtraction * -# @ref CLGEMMLowpMatrixMultiplyCore Quantized matrix multiplication core. Accumulators are 32-bit integers * -# @ref CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint Convert 32-bit integers into QSYMM16 @@ -78,10 +80,11 @@ public: * @param[in] forget_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: S32. * @param[in] cell_bias 1D weights tensor with dimensions [num_units]. Data type supported: S32. * @param[in] output_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: S32. - * @param[in] cell_state_in 2D tensor with dimensions [output_size, batch_size]. Data type supported: QSYMM16. - * @param[in] output_state_in 2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input. - * @param[out] cell_state_out Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size]. Data type supported: QSYMM16. - * @param[out] output_state_out Destination tensor. Output is a 2D tensor with dimensions [num_units, batch_size].Data types supported: Same as @p input. + * @param[in] cell_state_in 2D tensor with dimensions [num_units, batch_size]. Data type supported: QSYMM16. + * @param[in] output_state_in 2D tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input. + * @param[out] cell_state_out Destination tensor. Output is a 2D tensor with dimensions [num_units, batch_size]. Data type supported: QSYMM16. + * @param[out] output_state_out Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].Data types supported: Same as @p input. + * @param[out] output Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].Data types supported: Same as @p input. * @param[in] lstm_params Weights tensors used in peephole, CIFG and layer normalization optimizations: * input_intermediate_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at input gate. * forget_intermediate_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at forget gate. @@ -111,7 +114,7 @@ public: const ICLTensor *recurrent_to_forget_weights, const ICLTensor *recurrent_to_cell_weights, const ICLTensor *recurrent_to_output_weights, const ICLTensor *forget_gate_bias, const ICLTensor *cell_bias, const ICLTensor *output_gate_bias, const ICLTensor *cell_state_in, const ICLTensor *output_state_in, - ICLTensor *cell_state_out, ICLTensor *output_state_out, + ICLTensor *cell_state_out, ICLTensor *output_state_out, ICLTensor *output, const LSTMParams<ICLTensor> &lstm_params); /** Initialize function's tensors. @@ -127,10 +130,11 @@ public: * @param[in] forget_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: S32. * @param[in] cell_bias 1D weights tensor with dimensions [num_units]. Data type supported: S32. * @param[in] output_gate_bias 1D weights tensor with dimensions [num_units]. Data type supported: S32. - * @param[in] cell_state_in 2D tensor with dimensions [output_size, batch_size]. Data type supported: QSYMM16. - * @param[in] output_state_in 2D tensor with dimensions [num_units, batch_size]. Data type supported: Same as @p input. - * @param[out] cell_state_out Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size]. Data type supported: QSYMM16. - * @param[out] output_state_out Destination tensor. Output is a 2D tensor with dimensions [num_units, batch_size].Data types supported: Same as @p input. + * @param[in] cell_state_in 2D tensor with dimensions [num_units, batch_size]. Data type supported: QSYMM16. + * @param[in] output_state_in 2D tensor with dimensions [output_size, batch_size]. Data type supported: Same as @p input. + * @param[out] cell_state_out Destination tensor. Output is a 2D tensor with dimensions [num_units, batch_size]. Data type supported: QSYMM16. + * @param[out] output_state_out Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].Data types supported: Same as @p input. + * @param[out] output Destination tensor. Output is a 2D tensor with dimensions [output_size, batch_size].Data types supported: Same as @p input. * @param[in] lstm_params Weights tensors used in peephole, CIFG and layer normalization optimizations: * input_intermediate_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at input gate. * forget_intermediate_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at forget gate. @@ -160,48 +164,49 @@ public: const ICLTensor *recurrent_to_forget_weights, const ICLTensor *recurrent_to_cell_weights, const ICLTensor *recurrent_to_output_weights, const ICLTensor *forget_gate_bias, const ICLTensor *cell_bias, const ICLTensor *output_gate_bias, const ICLTensor *cell_state_in, const ICLTensor *output_state_in, - ICLTensor *cell_state_out, ICLTensor *output_state_out, + ICLTensor *cell_state_out, ICLTensor *output_state_out, ICLTensor *output, const LSTMParams<ICLTensor> &lstm_params); /** Static function to check if given info will lead to a valid configuration of @ref CLQLSTMLayer * - * @param[in] input Source tensor info. Input is a 2D tensor info with dimensions [input_size, batch_size]. Data types supported: QASYMM8_SIGNED. - * @param[in] input_to_forget_weights 2D weights tensor info with dimensions [input_size, num_units]. Data type supported: QSYMM8. - * @param[in] input_to_cell_weights 2D weights tensor info with dimensions [input_size, num_units]. Data type supported: QSYMM8. - * @param[in] input_to_output_weights 2D weights tensor info with dimensions [input_size, num_units]. Data type supported: QSYMM8. - * @param[in] recurrent_to_forget_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: QSYMM8. - * @param[in] recurrent_to_cell_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: QSYMM8. - * @param[in] recurrent_to_output_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: QSYMM8. - * @param[in] forget_gate_bias 1D weights tensor info with dimensions [num_units]. Data type supported: S32. - * @param[in] cell_bias 1D weights tensor info with dimensions [num_units]. Data type supported: S32. - * @param[in] output_gate_bias 1D weights tensor info with dimensions [num_units]. Data type supported: S32. - * @param[in] cell_state_in 2D tensor info with dimensions [num_units, batch_size]. Data type supported: QSYMM16. - * @param[in] output_state_in 2D tensor info with dimensions [output_size, batch_size]. Data type supported: Same as @p input. - * @param[out] cell_state_out Destination tensor info. Output is a 2D tensor info with dimensions [num_units, batch_size]. Data type supported: QSYMM16. - * @param[out] output_state_out Destination tensor info. Output is a 2D tensor info with dimensions [output_size, batch_size].Data types supported: Same as @p input. - * @param[in] lstm_params Weights tensors info used in peephole, CIFG and layer normalization optimizations: - * input_intermediate_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at input gate. - * forget_intermediate_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at forget gate. - * cell_intermediate_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at cell gate. - * output_intermediate_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at output gate. - * hidden_state_zero The zero point of the hidden state. - * hidden_state_scale The scale of the hidden state. - * input_to_input_weights (Optional) 2D weights tensor with dimensions [input_size, num_units]. Data type supported: QSYMM8. - * recurrent_to_input_weights (Optional) 2D weights tensor with dimensions [output_size, num_units]. Data type supported: QSYMM8. - * cell_to_input_weights (Optional) 1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: QSYMM16. - * cell_to_forget_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: QSYMM16. - * cell_to_output_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: QSYMM16. - * input_gate_bias (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: S32. - * projection_weights (Optional) 2D weights tensor with dimensions [output_size, num_units]. Data type supported: QSYMM8. - * projection_bias (Optional) 1D weights tensor with dimensions [output_size]. S32. - * input_layer_norm_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: QSYMM16. - * forget_layer_norm_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: QSYMM16. - * cell_layer_norm_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: QSYMM16. - * output_layer_norm_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: QSYMM16. - * cell_threshold (Optional) The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip]. - * If set to 0.0 then clipping is disabled. - * projection_threshold (Optional) The clipping threshold for the output from the projection layer, such that values are bound within - * [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled. + * @param[in] input Source tensor info. Input is a 2D tensor info with dimensions [input_size, batch_size]. Data types supported: QASYMM8_SIGNED. + * @param[in] input_to_forget_weights 2D weights tensor info with dimensions [input_size, num_units]. Data type supported: QSYMM8. + * @param[in] input_to_cell_weights 2D weights tensor info with dimensions [input_size, num_units]. Data type supported: QSYMM8. + * @param[in] input_to_output_weights 2D weights tensor info with dimensions [input_size, num_units]. Data type supported: QSYMM8. + * @param[in] recurrent_to_forget_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: QSYMM8. + * @param[in] recurrent_to_cell_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: QSYMM8. + * @param[in] recurrent_to_output_weights 2D weights tensor info with dimensions [output_size, num_units]. Data type supported: QSYMM8. + * @param[in] forget_gate_bias 1D weights tensor info with dimensions [num_units]. Data type supported: S32. + * @param[in] cell_bias 1D weights tensor info with dimensions [num_units]. Data type supported: S32. + * @param[in] output_gate_bias 1D weights tensor info with dimensions [num_units]. Data type supported: S32. + * @param[in] cell_state_in 2D tensor info with dimensions [num_units, batch_size]. Data type supported: QSYMM16. + * @param[in] output_state_in 2D tensor info with dimensions [output_size, batch_size]. Data type supported: Same as @p input. + * @param[in] cell_state_out Destination tensor info. Output is a 2D tensor info with dimensions [num_units, batch_size]. Data type supported: QSYMM16. + * @param[in] output_state_out Destination tensor info. Output is a 2D tensor info with dimensions [output_size, batch_size].Data types supported: Same as @p input. + * @param[in] output Destination tensor info. Output is a 2D tensor info with dimensions [output_size, batch_size].Data types supported: Same as @p input. + * @param[in] lstm_params Weights tensors info used in peephole, CIFG and layer normalization optimizations: + * input_intermediate_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at input gate. + * forget_intermediate_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at forget gate. + * cell_intermediate_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at cell gate. + * output_intermediate_scale Scale of the intermediate result of matmul, i.e. input to layer normalization, at output gate. + * hidden_state_zero The zero point of the hidden state. + * hidden_state_scale The scale of the hidden state. + * input_to_input_weights (Optional) 2D weights tensor with dimensions [input_size, num_units]. Data type supported: QSYMM8. + * recurrent_to_input_weights (Optional) 2D weights tensor with dimensions [output_size, num_units]. Data type supported: QSYMM8. + * cell_to_input_weights (Optional) 1D weights tensor with dimensions [num_units]. Can be nullptr. Data type supported: QSYMM16. + * cell_to_forget_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: QSYMM16. + * cell_to_output_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: QSYMM16. + * input_gate_bias (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: S32. + * projection_weights (Optional) 2D weights tensor with dimensions [output_size, num_units]. Data type supported: QSYMM8. + * projection_bias (Optional) 1D weights tensor with dimensions [output_size]. S32. + * input_layer_norm_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: QSYMM16. + * forget_layer_norm_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: QSYMM16. + * cell_layer_norm_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: QSYMM16. + * output_layer_norm_weights (Optional) 1D weights tensor with dimensions [num_units]. Data type supported: QSYMM16. + * cell_threshold (Optional) The clipping threshold for the cell state, such that values are bound within [-cell_clip, cell_clip]. + * If set to 0.0 then clipping is disabled. + * projection_threshold (Optional) The clipping threshold for the output from the projection layer, such that values are bound within + * [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled. * @return a status */ static Status validate(const ITensorInfo *input, @@ -209,7 +214,7 @@ public: const ITensorInfo *recurrent_to_forget_weights, const ITensorInfo *recurrent_to_cell_weights, const ITensorInfo *recurrent_to_output_weights, const ITensorInfo *forget_gate_bias, const ITensorInfo *cell_bias, const ITensorInfo *output_gate_bias, const ITensorInfo *cell_state_in, const ITensorInfo *output_state_in, - const ITensorInfo *cell_state_out, const ITensorInfo *output_state_out, + const ITensorInfo *cell_state_out, const ITensorInfo *output_state_out, const ITensorInfo *output, const LSTMParams<ITensorInfo> &lstm_params); // Inherited methods overridden: @@ -314,6 +319,7 @@ private: CLSaturatedArithmeticOperationKernel _accumulate_projection{}; CLActivationLayer _projection_clip{}; std::array<CLQLSTMLayerNormalizationKernel, _layer_norm_count> _layer_norms{ {} }; + CLCopyKernel _copy_output{}; // Tensor pointers const ICLTensor *_input_to_input_weights |