diff options
Diffstat (limited to 'arm_compute')
5 files changed, 10 insertions, 10 deletions
diff --git a/arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h b/arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h index 62f55fa91e..012ae1b2b7 100644 --- a/arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h +++ b/arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h @@ -59,7 +59,7 @@ public: * * Strides: only unit strides * - * @param[in] input Source tensor. The input is a 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] (NCHW data layout) or [IFM, kernel_x, kernel_y, OFM] (NHWC data layout). Data types supported: F32. + * @param[in] input Source tensor. The input is a 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] (NCHW data layout) or [IFM, kernel_x, kernel_y, OFM] (NHWC data layout). Data types supported: F16/F32. * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_filter_transform_shape. Data types supported: Same as @p input * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo */ @@ -77,7 +77,7 @@ public: * * Strides: only unit strides * - * @param[in] input Source tensor. The input is a 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] (NCHW data layout) or [IFM, kernel_x, kernel_y, OFM] (NHWC data layout). Data types supported: F32. + * @param[in] input Source tensor. The input is a 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] (NCHW data layout) or [IFM, kernel_x, kernel_y, OFM] (NHWC data layout). Data types supported: F16/F32. * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_filter_transform_shape. Data types supported: Same as @p input * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo * diff --git a/arm_compute/core/CL/kernels/CLWinogradInputTransformKernel.h b/arm_compute/core/CL/kernels/CLWinogradInputTransformKernel.h index 517b348ffb..bc05a0ebf1 100644 --- a/arm_compute/core/CL/kernels/CLWinogradInputTransformKernel.h +++ b/arm_compute/core/CL/kernels/CLWinogradInputTransformKernel.h @@ -57,7 +57,7 @@ public: * * Strides: only unit strides * - * @param[in] input The input tensor to transform. Data types supported: F32 + * @param[in] input The input tensor to transform. Data types supported: F16/F32 * @param[in] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_input_transform_shape. Data types supported: Same as @p input * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo. */ @@ -75,7 +75,7 @@ public: * * Strides: only unit strides * - * @param[in] input The input tensor to transform. Data types supported: F32 + * @param[in] input The input tensor to transform. Data types supported: F16/F32 * @param[in] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_input_transform_shape. Data types supported: Same as @p input * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo. * diff --git a/arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h b/arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h index bab93de4b0..3bbbb5834c 100644 --- a/arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h +++ b/arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h @@ -59,7 +59,7 @@ public: * * Strides: only unit strides * - * @param[in] input Source tensor with shape [C, N, K, batches]. Data types supported: F32. + * @param[in] input Source tensor with shape [C, N, K, batches]. Data types supported: F16/F32. * @param[in] bias Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. It can be a nullptr. Data type supported: as @p input * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_output_transform_shape. Data types supported: Same as @p input * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo @@ -78,7 +78,7 @@ public: * * Strides: only unit strides * - * @param[in] input Source tensor with shape [C, N, K, batches]. Data types supported: F32. + * @param[in] input Source tensor with shape [C, N, K, batches]. Data types supported: F16/F32. * @param[in] bias Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. It can be a nullptr. Data type supported: as @p input * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_output_transform_shape. Data types supported: Same as @p input * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo diff --git a/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h index a24ae31d41..395f59500b 100644 --- a/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h +++ b/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h @@ -64,7 +64,7 @@ public: * * @param[in] input Source tensor. 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: F32. + * Data types supported: F16/F32. * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input. * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].Data type supported: Same as @p input * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. @@ -83,7 +83,7 @@ public: * * @param[in] input Source tensor. 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: F32. + * Data types supported: F16/F32. * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input. * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].Data type supported: Same as @p input * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. diff --git a/arm_compute/runtime/CL/functions/CLWinogradInputTransform.h b/arm_compute/runtime/CL/functions/CLWinogradInputTransform.h index 8ea25a116a..71b4ea4faa 100644 --- a/arm_compute/runtime/CL/functions/CLWinogradInputTransform.h +++ b/arm_compute/runtime/CL/functions/CLWinogradInputTransform.h @@ -50,7 +50,7 @@ public: * * Strides: only unit strides * - * @param[in] input The input tensor to transform. Data types supported: F32 + * @param[in] input The input tensor to transform. Data types supported: F16,F32 * @param[in] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_input_transform_shape. Data types supported: Same as @p input * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo. */ @@ -68,7 +68,7 @@ public: * * Strides: only unit strides * - * @param[in] input The input tensor to transform. Data types supported: F32 + * @param[in] input The input tensor to transform. Data types supported: F16,F32 * @param[in] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_input_transform_shape. Data types supported: Same as @p input * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo. * |