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-rw-r--r--arm_compute/runtime/CL/functions/CLDirectDeconvolutionLayer.h15
1 files changed, 15 insertions, 0 deletions
diff --git a/arm_compute/runtime/CL/functions/CLDirectDeconvolutionLayer.h b/arm_compute/runtime/CL/functions/CLDirectDeconvolutionLayer.h
index 6632bfce80..1fed460e69 100644
--- a/arm_compute/runtime/CL/functions/CLDirectDeconvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLDirectDeconvolutionLayer.h
@@ -98,6 +98,21 @@ public:
*
*/
void configure(ICLTensor *input, ICLTensor *weights, const ICLTensor *bias, ICLTensor *output, const PadStrideInfo &info, const WeightsInfo &weights_info = WeightsInfo());
+ /** Set the input, weights, biases and output tensors.
+ *
+ * @param[in] compile_context The compile context to be used.
+ * @param[in,out] input Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs.
+ * Data types supported: QASYMM8_SIGNED/QASYMM8/F16/F32.
+ * @param[in] weights The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input.
+ * @param[in] bias (Optional) The biases have one dimension.
+ * Data type supported: Should match @p input data type, except for input of QASYMM8 and QASYMM8_SIGNED type where biases should be of S32 type
+ * @param[out] output Output tensor. The output has the same number of dimensions as the @p input.
+ * @param[in] info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo.
+ * @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer, specifies if the weights tensor has been reshaped with @ref CLWeightsReshapeKernel.
+ *
+ */
+ void configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *weights, const ICLTensor *bias, ICLTensor *output, const PadStrideInfo &info,
+ const WeightsInfo &weights_info = WeightsInfo());
/** Static function to check if given info will lead to a valid configuration of @ref CLDirectDeconvolutionLayer
*
* @param[in] input Input tensor info. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs.