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Diffstat (limited to 'arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h')
-rw-r--r--arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h10
1 files changed, 5 insertions, 5 deletions
diff --git a/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h b/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h
index bdc5792641..59740b9db9 100644
--- a/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h
+++ b/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -69,9 +69,9 @@ public:
/** Set the input and output of the kernel.
*
* @param[in] input The input tensor to convert. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] if shared,
- * and 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches] if unshared. Data types supported: QASYMM8/F16/F32
+ * and 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches] if unshared. Data types supported: All
* @param[in] biases The shared biases tensor to append. Bias is 1D tensor with dimensions [OFM] if shared and 2D tensor with
- * dimensions [OFM, num_patches] if unshared. Data types supported: Same as @p input
+ * dimensions [OFM, num_patches] if unshared. Data types supported: F16/F32, for quantized types this must be nullptr.
* @warning Appending biases to weights reshaped matrix is not supported for quantized asymmetric types.
* @param[out] output The output tensor. Should be a 2D Tensor if there are no groups and the weights are not shared; a 3D Tensor otherwise.
* Data types supported: Same as @p input
@@ -82,9 +82,9 @@ public:
/** Static function to check if given info will lead to a valid configuration of @ref CLWeightsReshapeKernel
*
* @param[in] input The input tensor to convert. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] if shared,
- * and 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches] if unshared. Data types supported: QASYMM8/F16/F32
+ * and 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches] if unshared. Data types supported: All
* @param[in] biases The shared biases tensor to append. Bias is 1D tensor with dimensions [OFM] if shared and 2D tensor with
- * dimensions [OFM, num_patches] if unshared. Data types supported: Same as @p input
+ * dimensions [OFM, num_patches] if unshared. Data types supported: F16/F32, for quantized types this must be nullptr.
* @warning Appending biases to weights reshaped matrix is not supported for quantized asymmetric types.
* @param[in] output The output tensor. Should be a 2D Tensor if there are no groups and the weights are not shared; a 3D Tensor otherwise.
* Data types supported: Same as @p input