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Diffstat (limited to 'arm_compute/runtime/NEON/functions/NEConvertFullyConnectedWeights.h')
-rw-r--r--arm_compute/runtime/NEON/functions/NEConvertFullyConnectedWeights.h5
1 files changed, 3 insertions, 2 deletions
diff --git a/arm_compute/runtime/NEON/functions/NEConvertFullyConnectedWeights.h b/arm_compute/runtime/NEON/functions/NEConvertFullyConnectedWeights.h
index 37b6b6c4dd..42f787090e 100644
--- a/arm_compute/runtime/NEON/functions/NEConvertFullyConnectedWeights.h
+++ b/arm_compute/runtime/NEON/functions/NEConvertFullyConnectedWeights.h
@@ -32,6 +32,7 @@
namespace arm_compute
{
+// Forward declarations
class ITensor;
/** Basic function to run @ref NEConvertFullyConnectedWeightsKernel. */
@@ -42,7 +43,7 @@ public:
NEConvertFullyConnectedWeights();
/** Initialize the function.
*
- * @param[in] input Source weights tensor to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32.
+ * @param[in] input Source weights tensor to convert. Must be 2 dimensional. Data types supported: All.
* @param[out] output The converted weights tensor. Shape and Data Type: Same as @p input.
* @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer).
* @param[in] data_layout The data layout the weights have been trained in.
@@ -50,7 +51,7 @@ public:
void configure(const ITensor *input, ITensor *output, const TensorShape &original_input_shape, DataLayout data_layout);
/** Static function to check if given info will lead to a valid configuration of @ref NEConvertFullyConnectedWeights
*
- * @param[in] input Source weights tensor info to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32.
+ * @param[in] input Source weights tensor info to convert. Must be 2 dimensional. Data types supported: All.
* @param[in] output The converted weights tensor info. Shape and Data Type: Same as @p input.
* @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer).
* @param[in] data_layout The data layout the weights have been trained in.