diff options
Diffstat (limited to 'arm_compute/runtime/CL/functions/CLRNNLayer.h')
| -rw-r--r-- | arm_compute/runtime/CL/functions/CLRNNLayer.h | 15 |
1 files changed, 14 insertions, 1 deletions
diff --git a/arm_compute/runtime/CL/functions/CLRNNLayer.h b/arm_compute/runtime/CL/functions/CLRNNLayer.h index 569e3da89e..0291eb17a9 100644 --- a/arm_compute/runtime/CL/functions/CLRNNLayer.h +++ b/arm_compute/runtime/CL/functions/CLRNNLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2019 ARM Limited. + * Copyright (c) 2018-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -54,6 +54,19 @@ public: void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *recurrent_weights, const ICLTensor *bias, ICLTensor *hidden_state, ICLTensor *output, ActivationLayerInfo &info); /** Initialize the function * + * @param[in] compile_context The compile context to be used. + * @param[in] input Input is a 2-D tensor of shape [input_size, batch_size]. Data types supported: F16/F32 + * @param[in] weights Weights tensor of shape [input_size, num_units] that multiplies the input. Data types supported: Same as @p input + * @param[in] recurrent_weights Weights tensor of shape [num_units, num_units] that multiplies the current 'state'. Data types supported: Same as @p input + * @param[in] bias Bias vector of shape [num_units]. Data types supported: Same as @p input + * @param[out] output Output tensor of shape [num_units, batch_size]. Data types supported: Same as @p input + * @param[in,out] hidden_state Output tensor of shape [num_units, batch_size]. Data types supported: Same as @p input + * @param[in] info Activation layer parameter. + */ + void 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); + /** Initialize the function + * * @param[in] input Input is a 2-D tensor of shape [input_size, batch_size]. Data types supported: F16/F32 * @param[in] weights Weights tensor of shape [input_size, num_units] that multiplies the input. Data types supported: Same as @p input * @param[in] recurrent_weights Weights tensor of shape [num_units, num_units] that multiplies the current 'state'. Data types supported: Same as @p input |