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| author | Vidhya Sudhan Loganathan <vidhyasudhan.loganathan@arm.com> | 2018-11-16 11:33:12 +0000 |
|---|---|---|
| committer | Georgios Pinitas <georgios.pinitas@arm.com> | 2018-11-16 17:37:40 +0000 |
| commit | a25d16c86f0d870408bc8b941aa755093417b0f0 (patch) | |
| tree | b62d145a4e5009d894262a7ffa66cdba8260bb03 /arm_compute/core/Types.h | |
| parent | a7b54f44e2bf133179f24a34007bc93237dd2265 (diff) | |
| download | ComputeLibrary-a25d16c86f0d870408bc8b941aa755093417b0f0.tar.gz | |
COMPMID-1266 : Add support for FP16 in CLWinogradConvolutionLayer: 5x5 kernels
Introduced F32 accumulation for F16 winograd gemm and output transform
WinogradConvolution will be available for F16 only if fast math flag is enabled
Change-Id: I215593c205236a0f9669218437bb40b184ec6a4f
Diffstat (limited to 'arm_compute/core/Types.h')
| -rw-r--r-- | arm_compute/core/Types.h | 17 |
1 files changed, 14 insertions, 3 deletions
diff --git a/arm_compute/core/Types.h b/arm_compute/core/Types.h index fb277584fd..4eb8129b62 100644 --- a/arm_compute/core/Types.h +++ b/arm_compute/core/Types.h @@ -1593,7 +1593,8 @@ class GEMMInfo public: /** Default constructor */ GEMMInfo() - : _is_a_reshaped(false), _is_b_reshaped(false), _reshape_b_only_on_first_run(false), _depth_output_gemm3d(0), _reinterpret_input_as_3d(false), _retain_internal_weights(false), _gemmlowp_output_stage() + : _is_a_reshaped(false), _is_b_reshaped(false), _reshape_b_only_on_first_run(false), _depth_output_gemm3d(0), _reinterpret_input_as_3d(false), _retain_internal_weights(false), + _gemmlowp_output_stage(), _fp_mixed_precision(false) { } /** Constructor @@ -1607,12 +1608,13 @@ public: * to perform 1x1 convolutions with the NHWC data layout) * @param[in] retain_internal_weights (Optional) Retain the weights tensor from previous run * @param[in] gemmlowp_output_stage (Optional) GEMMLowp Output stage info + * @param[in] fp_mixed_precision (Optional) Use wider accumulators (32 bit instead of 16 for FP16) to improve accuracy. * */ GEMMInfo(bool is_a_reshaped, bool is_b_reshaped, bool reshape_b_only_on_first_run, int depth_output_gemm3d = 0, bool reinterpret_input_as_3d = false, bool retain_internal_weights = false, - GEMMLowpOutputStageInfo gemmlowp_output_stage = GEMMLowpOutputStageInfo()) + GEMMLowpOutputStageInfo gemmlowp_output_stage = GEMMLowpOutputStageInfo(), bool fp_mixed_precision = false) : _is_a_reshaped(is_a_reshaped), _is_b_reshaped(is_b_reshaped), _reshape_b_only_on_first_run(reshape_b_only_on_first_run), _depth_output_gemm3d(depth_output_gemm3d), - _reinterpret_input_as_3d(reinterpret_input_as_3d), _retain_internal_weights(retain_internal_weights), _gemmlowp_output_stage(gemmlowp_output_stage) + _reinterpret_input_as_3d(reinterpret_input_as_3d), _retain_internal_weights(retain_internal_weights), _gemmlowp_output_stage(gemmlowp_output_stage), _fp_mixed_precision(fp_mixed_precision) { } /** Flag which specifies if the matrix A has been reshaped @@ -1673,6 +1675,14 @@ public: { return _gemmlowp_output_stage; }; + /** Flag which specifies if a wider accumulator should be used. + * + * @return True if a wider accumulator has to be used + */ + bool fp_mixed_precision() const + { + return _fp_mixed_precision; + }; private: const bool _is_a_reshaped; @@ -1682,6 +1692,7 @@ private: const bool _reinterpret_input_as_3d; const bool _retain_internal_weights; const GEMMLowpOutputStageInfo _gemmlowp_output_stage; + const bool _fp_mixed_precision; }; /** Winograd information */ |