diff options
Diffstat (limited to 'arm_compute/runtime/CL/functions/CLQLSTMLayer.h')
| -rw-r--r-- | arm_compute/runtime/CL/functions/CLQLSTMLayer.h | 72 |
1 files changed, 61 insertions, 11 deletions
diff --git a/arm_compute/runtime/CL/functions/CLQLSTMLayer.h b/arm_compute/runtime/CL/functions/CLQLSTMLayer.h index ab34135ff5..72a61f8505 100644 --- a/arm_compute/runtime/CL/functions/CLQLSTMLayer.h +++ b/arm_compute/runtime/CL/functions/CLQLSTMLayer.h @@ -113,6 +113,55 @@ public: ICLTensor *cell_state_out, ICLTensor *output_state_out, const LSTMParams<ICLTensor> &lstm_params); + /** Initialize function's tensors. + * + * @param[in] compile_context The compile context to be used. + * @param[in] input Source tensor. Input is a 2D tensor with dimensions [input_size, batch_size]. Data types supported: QASYMM8_SIGNED. + * @param[in] input_to_forget_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: QSYMM8. + * @param[in] input_to_cell_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: QSYMM8. + * @param[in] input_to_output_weights 2D weights tensor with dimensions [input_size, num_units]. Data type supported: QSYMM8. + * @param[in] recurrent_to_forget_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: QSYMM8. + * @param[in] recurrent_to_cell_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: QSYMM8. + * @param[in] recurrent_to_output_weights 2D weights tensor with dimensions [output_size, num_units]. Data type supported: QSYMM8. + * @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] 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. + * 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. + */ + void configure(const CLCompileContext &compile_context, const ICLTensor *input, + const ICLTensor *input_to_forget_weights, const ICLTensor *input_to_cell_weights, const ICLTensor *input_to_output_weights, + 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, + 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. @@ -169,19 +218,20 @@ public: private: /** Internal method to configure matrix multiplication plus output stage of each gate. * - * @param[in] mm Matrix multiplication function to use. - * @param[in] outstage Output stage function to use. - * @param[in] gemmlowp_info GEMMLowp metadata to be used by the output stage. - * @param[in] mm_input Input tensor to matrix multiplication function. - * @param[in] mm_weights Weights tensor to matrix multiplication function. - * @param[in] bias Bias tensor to matrix multiplication function. - * @param[in] outstage_res Tensor to be used for storing the result of the output stage. - * @param[in] gemmlowp_scale Real multiplier to be used computing multiplier and shift for requantization. - * @param[in] mm_res_info Tensor info to be used to initialize matrix multiplication result tensor. - * @param[in] mm_res_info Tensor info to be used to initialize output stage result tensor. + * @param[in] compile_context The compile context to be used. + * @param[in] mm Matrix multiplication function to use. + * @param[in] outstage Output stage function to use. + * @param[in] gemmlowp_info GEMMLowp metadata to be used by the output stage. + * @param[in] mm_input Input tensor to matrix multiplication function. + * @param[in] mm_weights Weights tensor to matrix multiplication function. + * @param[in] bias Bias tensor to matrix multiplication function. + * @param[in] outstage_res Tensor to be used for storing the result of the output stage. + * @param[in] gemmlowp_scale Real multiplier to be used computing multiplier and shift for requantization. + * @param[in] mm_res_info Tensor info to be used to initialize matrix multiplication result tensor. + * @param[in] mm_res_info Tensor info to be used to initialize output stage result tensor. * */ - void configure_mm(CLGEMMLowpMatrixMultiplyCore &mm, CLGEMMLowpOutputStage &outstage, GEMMLowpOutputStageInfo &gemmlowp_info, + void configure_mm(const CLCompileContext &compile_context, CLGEMMLowpMatrixMultiplyCore &mm, CLGEMMLowpOutputStage &outstage, GEMMLowpOutputStageInfo &gemmlowp_info, const ICLTensor *mm_input, const ICLTensor *mm_weights, const ICLTensor *bias, CLTensor *mm_res, CLTensor *outstage_res, float gemmlowp_scale, const TensorInfo &mm_res_info, const TensorInfo &outstage_tensor_info); |