diff options
Diffstat (limited to 'arm_compute/runtime')
| -rw-r--r-- | arm_compute/runtime/NEON/functions/NEFuseBatchNormalization.h | 50 |
1 files changed, 28 insertions, 22 deletions
diff --git a/arm_compute/runtime/NEON/functions/NEFuseBatchNormalization.h b/arm_compute/runtime/NEON/functions/NEFuseBatchNormalization.h index 5e6286966a..3a2f6ccb6d 100644 --- a/arm_compute/runtime/NEON/functions/NEFuseBatchNormalization.h +++ b/arm_compute/runtime/NEON/functions/NEFuseBatchNormalization.h @@ -52,37 +52,43 @@ public: ~NEFuseBatchNormalization() = default; /** Set the input and output tensors. * - * @param[in] conv_weights Convolution layer weights tensor. Data type supported: F16/F32 - * @param[in] bn_mean Batch normalization layer mean tensor. Same as @p conv_weights - * @param[in] bn_var Batch normalization layer variance tensor. Same as @p conv_weights - * @param[out] fused_weights Output fused weights tensor. Same as @p conv_weights - * @param[out] fused_bias Output fused bias tensor. Same as @p conv_weights - * @param[in] conv_bias (Optional) Convolution layer bias tensor. Same as @p conv_weights - * @param[in] bn_beta (Optional) Batch normalization layer beta tensor. Same as @p conv_weights - * @param[in] bn_gamma (Optional) Batch normalization layer gamma tensor. Same as @p conv_weights + * @param[in] input_weights Input weights tensor for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC + * @param[in] bn_mean Batch normalization layer mean tensor. Same as @p input_weights + * @param[in] bn_var Batch normalization layer variance tensor. Same as @p input_weights + * @param[out] fused_weights (Optional) Output fused weights tensor. It can be a nullptr in case of in-place computation. Same as @p input_weights + * @param[out] fused_bias (Optional) Output fused bias tensor. It can be a nullptr in case of in-place computation and input_bias != nullptr. Same as @p input_weights + * @param[in] input_bias (Optional) Input bias tensor for convolution or depthwise convolution layer. It can be a nullptr in case the bias tensor is not required. Same as @p input_weights + * @param[in] bn_beta (Optional) Batch normalization layer beta tensor. It can be a nullptr in case the beta tensor is not required. Same as @p input_weights + * @note if nullptr, bn_beta is set to 0.0 + * @param[in] bn_gamma (Optional) Batch normalization layer gamma tensor. It can be a nullptr in case the gamma tensor is not required. Same as @p input_weights + * @note if nullptr, bn_gamma is set to 1.0 * @param[in] epsilon (Optional) Batch normalization layer epsilon parameter. Defaults to 0.001f. + * @param[in] fbn_type (Optional) Fused batch normalization type. Defaults to Convolution. */ - void configure(const ITensor *conv_weights, const ITensor *bn_mean, const ITensor *bn_var, ITensor *fused_weights, ITensor *fused_bias, - const ITensor *conv_bias = nullptr, const ITensor *bn_beta = nullptr, const ITensor *bn_gamma = nullptr, - float epsilon = 0.001f); + void configure(const ITensor *input_weights, const ITensor *bn_mean, const ITensor *bn_var, ITensor *fused_weights, ITensor *fused_bias, + const ITensor *input_bias = nullptr, const ITensor *bn_beta = nullptr, const ITensor *bn_gamma = nullptr, + float epsilon = 0.001f, FuseBatchNormalizationType fbn_type = FuseBatchNormalizationType::CONVOLUTION); /** Static function to check if given info will lead to a valid configuration of @ref NEFuseBatchNormalization * - * @param[in] conv_weights Convolution layer weights tensor. Data type supported: F16/F32 - * @param[in] bn_mean Batch normalization layer mean tensor. Same as @p conv_weights - * @param[in] bn_var Batch normalization layer variance tensor. Same as @p conv_weights - * @param[in] fused_weights Output fused weights tensor. Same as @p conv_weights - * @param[in] fused_bias Output fused bias tensor. Same as @p conv_weights - * @param[in] conv_bias (Optional) Convolution layer bias tensor. Same as @p conv_weights - * @param[in] bn_beta (Optional) Batch normalization layer beta tensor. Same as @p conv_weights - * @param[in] bn_gamma (Optional) Batch normalization layer gamma tensor. Same as @p conv_weights + * @param[in] input_weights Input weights tensor info for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC + * @param[in] bn_mean Batch normalization layer mean tensor info. Same as @p input_weights + * @param[in] bn_var Batch normalization layer variance tensor info. Same as @p input_weights + * @param[in] fused_weights (Optional) Output fused weights tensor info. It can be a nullptr in case of in-place computation. Same as @p input_weights + * @param[in] fused_bias (Optional) Output fused bias tensor info. It can be a nullptr in case of in-place computation and input_bias != nullptr. Same as @p input_weights + * @param[in] input_bias (Optional) Input bias tensor info for convolution or depthwise convolution layer. It can be a nullptr in case the bias tensor is not required. Same as @p input_weights + * @param[in] bn_beta (Optional) Batch normalization layer beta tensor info. It can be a nullptr in case the beta tensor is not required. Same as @p input_weights + * @note if nullptr, bn_beta is set to 0.0 + * @param[in] bn_gamma (Optional) Batch normalization layer gamma tensor info. It can be a nullptr in case the gamma tensor is not required. Same as @p input_weights + * @note if nullptr, bn_gamma is set to 1.0 * @param[in] epsilon (Optional) Batch normalization layer epsilon parameter. Defaults to 0.001f. + * @param[in] fbn_type (Optional) Fused batch normalization type. Defaults to Convolution. * * @return a status */ - static Status validate(const ITensorInfo *conv_weights, const ITensorInfo *bn_mean, const ITensorInfo *bn_var, + static Status validate(const ITensorInfo *input_weights, const ITensorInfo *bn_mean, const ITensorInfo *bn_var, const ITensorInfo *fused_weights, const ITensorInfo *fused_bias, - const ITensorInfo *conv_bias = nullptr, const ITensorInfo *bn_beta = nullptr, const ITensorInfo *bn_gamma = nullptr, - float epsilon = 0.001f); + const ITensorInfo *input_bias = nullptr, const ITensorInfo *bn_beta = nullptr, const ITensorInfo *bn_gamma = nullptr, + float epsilon = 0.001f, FuseBatchNormalizationType fbn_type = FuseBatchNormalizationType::CONVOLUTION); // Inherited methods overridden: void run() override; |