[arm_gemm] Import fixed-format kernels from gemm_linux.
This is a No Functional Change Intended (NFCI) patch. It imports the
kernel in the code, but the interface to select them and expose the
format of the weight tensors to the user will be provided in a
subsequent patch.
Kernels and kernel selection code in arm_gemm has been provided
by David.Mansell <David.Mansell@arm.com>.
The kernels are not compiled in the library by default, but need to be
selected via the `scons` option `experimental_fixed_format_kernels=1`.
Resolves: ONCPUML-829
Signed-off-by: Francesco.Petrogalli@arm.com <francesco.petrogalli@arm.com>
Change-Id: If00ccb2b9b7221e01b214cf9783111226ccc8bf4
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7380
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/core/Types.h b/arm_compute/core/Types.h
index 7ae6a7e..b1a1eb6 100644
--- a/arm_compute/core/Types.h
+++ b/arm_compute/core/Types.h
@@ -774,10 +774,10 @@
private:
std::pair<unsigned int, unsigned int> _stride;
- unsigned int _pad_left;
- unsigned int _pad_top;
- unsigned int _pad_right;
- unsigned int _pad_bottom;
+ unsigned int _pad_left;
+ unsigned int _pad_top;
+ unsigned int _pad_right;
+ unsigned int _pad_bottom;
DimensionRoundingType _round_type;
};
@@ -919,14 +919,14 @@
}
private:
- std::vector<float> _min_sizes;
- std::vector<float> _variances;
- float _offset;
- bool _flip;
- bool _clip;
- std::vector<float> _max_sizes;
- std::vector<float> _aspect_ratios;
- Coordinates2D _img_size;
+ std::vector<float> _min_sizes;
+ std::vector<float> _variances;
+ float _offset;
+ bool _flip;
+ bool _clip;
+ std::vector<float> _max_sizes;
+ std::vector<float> _aspect_ratios;
+ Coordinates2D _img_size;
std::array<float, 2> _steps;
};
@@ -1171,15 +1171,15 @@
}
private:
- unsigned int _max_detections;
- unsigned int _max_classes_per_detection;
- float _nms_score_threshold;
- float _iou_threshold;
- unsigned int _num_classes;
+ unsigned int _max_detections;
+ unsigned int _max_classes_per_detection;
+ float _nms_score_threshold;
+ float _iou_threshold;
+ unsigned int _num_classes;
std::array<float, 4> _scales_values;
- bool _use_regular_nms;
- unsigned int _detection_per_class;
- bool _dequantize_scores;
+ bool _use_regular_nms;
+ unsigned int _detection_per_class;
+ bool _dequantize_scores;
};
/** Pooling Layer Information struct*/
@@ -1612,13 +1612,13 @@
}
private:
- float _img_width;
- float _img_height;
- float _scale;
- bool _apply_scale;
- bool _correct_transform_coords;
+ float _img_width;
+ float _img_height;
+ float _scale;
+ bool _apply_scale;
+ bool _correct_transform_coords;
std::array<float, 4> _weights;
- float _bbox_xform_clip;
+ float _bbox_xform_clip;
};
/** Activation Layer Information class */
@@ -2105,7 +2105,8 @@
_pretranspose_A(false),
_pretranspose_B(false),
_activation_info(),
- _post_ops()
+ _post_ops(),
+ _fixed_format(false)
{
}
/** Constructor
@@ -2124,10 +2125,12 @@
* @param[in] broadcast_bias (Optional) Broadcast the shape of the bias tensor from a vector to a matrix.
* @param[in] activation_info (Optional) Activation to apply after the matrix multiplication
* @param[in] post_ops (Optional) A sequence of post operations that are performed after the main operation.
+ * @param[in] fixed_format (Optional) Specify the selection of fixed format kernels for variable weights support in GEMM. These kernels expect the weights tensor to be in amemory format that is fixed by the kernel itself. For more information, see arm_gemm::WeightFormat.
*/
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(), bool fp_mixed_precision = false, bool fast_math = false, bool broadcast_bias = false,
- const ActivationLayerInfo &activation_info = ActivationLayerInfo(), const experimental::PostOpList<ITensorInfo *> &post_ops = experimental::PostOpList<ITensorInfo *>()) noexcept
+ const ActivationLayerInfo &activation_info = ActivationLayerInfo(), const experimental::PostOpList<ITensorInfo *> &post_ops = experimental::PostOpList<ITensorInfo *>(),
+ bool fixed_format = false) noexcept
: _is_a_reshaped(is_a_reshaped),
_is_b_reshaped(is_b_reshaped),
_reshape_b_only_on_first_run(reshape_b_only_on_first_run),
@@ -2141,7 +2144,8 @@
_pretranspose_A(false),
_pretranspose_B(false),
_activation_info(activation_info),
- _post_ops(post_ops)
+ _post_ops(post_ops),
+ _fixed_format(fixed_format)
{
}
/** Flag which specifies if the matrix A has been reshaped
@@ -2306,6 +2310,14 @@
{
_post_ops = post_ops;
}
+ /** Flag which specifies if the GEMM operation is running fixed-format kernels.
+ *
+ * @return True if the GEMM operation is running fixed-format kernel else false.
+ */
+ bool fixed_format() const
+ {
+ return _fixed_format;
+ }
private:
bool _is_a_reshaped;
@@ -2322,6 +2334,7 @@
bool _pretranspose_B;
ActivationLayerInfo _activation_info;
experimental::PostOpList<ITensorInfo *> _post_ops;
+ bool _fixed_format;
};
/** Winograd information */