COMPMID-3280: Make all ML primitives for CL use the new interface - Part 2
- CLFunctions have been updated
Change-Id: Ie3256a6c775bc12f3126482bd8e8a46da54b267c
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3053
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/runtime/CL/functions/CLCropResize.h b/arm_compute/runtime/CL/functions/CLCropResize.h
index 244e345..86df0d4 100644
--- a/arm_compute/runtime/CL/functions/CLCropResize.h
+++ b/arm_compute/runtime/CL/functions/CLCropResize.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2019 ARM Limited.
+ * Copyright (c) 2019-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -62,10 +62,10 @@
* @note Box indices may be outside of the bounds, in which case @p extrapolation_value is used.
* @note Start and end indices of boxes are inclusive.
*
- * @param[in] input Source tensor containing N batches of 3D images to be cropped. Data type supported: F32
- * @param[in] boxes Tensor containing the boxes used to crop the images. Data type supported: F32
+ * @param[in] input Source tensor containing N batches of 3D images to be cropped. Data type supported: : U16/S16/U32/S32/F16/F32
+ * @param[in] boxes Tensor containing the boxes used to crop the images. It has to be known before configuration. Data type supported: F32
* @param[in] box_ind One dimensional tensor containing the batch index of the 3D image in @p input that the corresponding
- * box in @p boxes will be applied to. Data type supported: F32
+ * box in @p boxes will be applied to. It has to be known before configuration. Data type supported: F32
* @param[out] output Destination tensor containing a cropped and resized image for each box in @p boxes. Data type supported: F32
* @param[in] crop_size The dimensions that each cropped image will be resized to.
* @param[in] method The policy to be used when resizing image. Default is bilinear.
@@ -73,6 +73,24 @@
*/
void configure(const ICLTensor *input, ICLTensor *boxes, ICLTensor *box_ind, ICLTensor *output, Coordinates2D crop_size,
InterpolationPolicy method = InterpolationPolicy::BILINEAR, float extrapolation_value = 0);
+ /** Configure kernel
+ *
+ * @note Supported tensor rank: up to 4
+ * @note Box indices may be outside of the bounds, in which case @p extrapolation_value is used.
+ * @note Start and end indices of boxes are inclusive.
+ *
+ * @param[in] compile_context The compile context to be used.
+ * @param[in] input Source tensor containing N batches of 3D images to be cropped. Data type supported: U16/S16/U32/S32/F16/F32
+ * @param[in] boxes Tensor containing the boxes used to crop the images. It has to be known before configuration. Data type supported: F32
+ * @param[in] box_ind One dimensional tensor containing the batch index of the 3D image in @p input that the corresponding
+ * box in @p boxes will be applied to. It has to be known before configuration. Data type supported: F32
+ * @param[out] output Destination tensor containing a cropped and resized image for each box in @p boxes. Data type supported: F32
+ * @param[in] crop_size The dimensions that each cropped image will be resized to.
+ * @param[in] method The policy to be used when resizing image. Default is bilinear.
+ * @param[in] extrapolation_value Value to be used for values outside of the image for cropping and resizing. Default is 0.
+ */
+ void configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *boxes, ICLTensor *box_ind, ICLTensor *output, Coordinates2D crop_size,
+ InterpolationPolicy method = InterpolationPolicy::BILINEAR, float extrapolation_value = 0);
/** Static function to check if given info will lead to a valid configuration of @ref NESlice
*
@@ -109,6 +127,8 @@
std::vector<std::unique_ptr<CLCopyKernel>> _copy;
std::vector<std::unique_ptr<CLTensor>> _crop_results;
std::vector<std::unique_ptr<CLTensor>> _scaled_results;
+
+ std::vector<std::unique_ptr<ICLKernel>> _internal_kernels;
};
} // namespace arm_compute
#endif /* ARM_COMPUTE_CL_CROP_RESIZE_H */