COMPMID-2244: Extend CLFuseBatchNormalization to support DepthwiseConvolution weights
Change-Id: I7d1907f35cc4899379073759be2f7cce24e51e9d
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1327
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/runtime/CL/functions/CLFuseBatchNormalization.h b/arm_compute/runtime/CL/functions/CLFuseBatchNormalization.h
index 4e7f1cb..50385d4 100644
--- a/arm_compute/runtime/CL/functions/CLFuseBatchNormalization.h
+++ b/arm_compute/runtime/CL/functions/CLFuseBatchNormalization.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -51,41 +51,43 @@
~CLFuseBatchNormalization() = 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. It can be a nullptr in case of in-place computation. Same as @p conv_weights
- * @param[out] fused_bias Output fused bias tensor. It can be a nullptr in case of in-place computation and conv_bias != nullptr. Same as @p conv_weights
- * @param[in] conv_bias (Optional) Convolution layer bias tensor. It can be a nullptr in case the bias tensor is not required. Same as @p conv_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 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 Output fused weights tensor. It can be a nullptr in case of in-place computation. Same as @p input_weights
+ * @param[out] fused_bias 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 conv_weights
+ * @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 ICLTensor *conv_weights, const ICLTensor *bn_mean, const ICLTensor *bn_var, ICLTensor *fused_weights, ICLTensor *fused_bias,
- const ICLTensor *conv_bias = nullptr, const ICLTensor *bn_beta = nullptr, const ICLTensor *bn_gamma = nullptr,
- float epsilon = 0.001f);
+ void configure(const ICLTensor *input_weights, const ICLTensor *bn_mean, const ICLTensor *bn_var, ICLTensor *fused_weights, ICLTensor *fused_bias,
+ const ICLTensor *input_bias = nullptr, const ICLTensor *bn_beta = nullptr, const ICLTensor *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 CLFuseBatchNormalization
*
- * @param[in] conv_weights Convolution layer weights tensor info. Data type supported: F16/F32
- * @param[in] bn_mean Batch normalization layer mean tensor info. Same as @p conv_weights
- * @param[in] bn_var Batch normalization layer variance tensor info. Same as @p conv_weights
- * @param[out] fused_weights Output fused weights tensor info. It can be a nullptr in case of in-place computation. Same as @p conv_weights
- * @param[out] fused_bias Output fused bias tensor info. It can be a nullptr in case of in-place computation and conv_bias != nullptr. Same as @p conv_weights
- * @param[in] conv_bias (Optional) Convolution layer bias tensor info. It can be a nullptr in case the bias tensor is not required. Same as @p conv_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 conv_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 conv_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] 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 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 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;