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-rw-r--r--arm_compute/runtime/NEON/functions/NEIm2Col.h36
1 files changed, 19 insertions, 17 deletions
diff --git a/arm_compute/runtime/NEON/functions/NEIm2Col.h b/arm_compute/runtime/NEON/functions/NEIm2Col.h
index cb08f5cd09..cf4999b5af 100644
--- a/arm_compute/runtime/NEON/functions/NEIm2Col.h
+++ b/arm_compute/runtime/NEON/functions/NEIm2Col.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -39,28 +39,30 @@ class NEIm2Col : public INESimpleFunction
public:
/** Configure the im2col NEON kernel
*
- * @param[in] input The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM],
- * while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QS8/QS16/QASYMM8/F16/F32
- * Note: QASYMM8 works only for has_bias = false
- * @param[out] output The output tensor. Data types supported: Same as @p input
- * @param[in] kernel_dims The kernel dimensions (width and height).
- * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
- * @param[in] has_bias In case biases are provided expands the matrix with 1.
+ * @param[in] input The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM],
+ * while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QS8/QS16/QASYMM8/F16/F32
+ * Note: QASYMM8 works only for has_bias = false
+ * @param[out] output The output tensor. Data types supported: Same as @p input
+ * @param[in] kernel_dims The kernel dimensions (width and height).
+ * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
+ * @param[in] has_bias In case biases are provided expands the matrix with 1.
+ * @param[in] is_fully_connected Determines whether this kernel will be called by @ref NEFullyConnectedLayer in order to validate the arguments
*/
- void configure(const ITensor *input, ITensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias);
+ void configure(const ITensor *input, ITensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, bool is_fully_connected = false);
/** Static function to check if given info will lead to a valid configuration of @ref NEIm2Col
*
- * @param[in] input The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM],
- * while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QS8/QS16/QASYMM8/F16/F32
- * Note: QASYMM8 works only for has_bias = false
- * @param[in] output The output tensor. Data types supported: Same as @p input
- * @param[in] kernel_dims The kernel dimensions (width and height).
- * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
- * @param[in] has_bias In case biases are provided expands the matrix with 1.
+ * @param[in] input The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM],
+ * while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QS8/QS16/QASYMM8/F16/F32
+ * Note: QASYMM8 works only for has_bias = false
+ * @param[in] output The output tensor. Data types supported: Same as @p input
+ * @param[in] kernel_dims The kernel dimensions (width and height).
+ * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
+ * @param[in] has_bias In case biases are provided expands the matrix with 1.
+ * @param[in] is_fully_connected Determines whether this kernel will be called by @ref NEFullyConnectedLayer in order to validate the arguments
*
* @return a status
*/
- static Status validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias);
+ static Status validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, bool is_fully_connected);
};
}
#endif /* __ARM_COMPUTE_NEIM2COL_H__ */