/*
-// Copyright (c) 2016 Intel Corporation
+// Copyright (c) 2016-2018 Intel Corporation
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
const char* engine_log; ///< Specifies a file to which engine log should be dumped. Null/empty values means no logging.
const char* sources_dumps_dir; ///< Specifies a directory where sources of cldnn::program objects should be dumped. Null/empty values means no loggins.
/*cldnn_priority_mode_type*/ int16_t priority_mode; ///< Priority mode (support of OpenCL priority hints in command queue).
- /*cldnn_throttle_mode_type*/ int16_t throttle_mode; ///< Placeholder for throttle mode (support of throttle hints in command queue). It has no effect for now and should be set to cldnn_throttle_disabled.
+ /*cldnn_throttle_mode_type*/ int16_t throttle_mode; ///< Throttle mode (support of throttle hints in command queue).
uint32_t enable_memory_pool; ///< Enables memory usage optimization. memory objects will be reused when possible.
+ void* context;
+ const char* tuning_cache_path; ///< Enables defining other than default path to tuning cache json
} cldnn_engine_configuration;
/// @brief Information about the engine returned by cldnn_get_engine_info().
cldnn_build_option_graph_dumps_dir, ///< Specifies a directory to which stages of network compilation should be dumped.
cldnn_build_option_serialization, ///< Specifies a name of files to which serialization should be dumped.
cldnn_build_option_load_program, ///< Specifies a name of load_program process.
- cldnn_build_option_learning_config ///< User defined learning parameters.
+ cldnn_build_option_learning_config, ///< User defined learning parameters.
+ cldnn_build_option_detection_output_gpu ///< Run detection output layer always on GPU, regardless performance
} cldnn_build_option_type;
/// @brief Tuning modes.
cldnn_format_fyxb, ///< format not used inside clDNN, but supported in reorder as extension for user provided formats.
cldnn_format_os_iyx_osv16, ///< format used only for convolution weights: os - output feature maps slice, i - input feature maps, yx - spatials, sv16 - 16 values of single slice.
///< \n \image html os_iyx_osv16.jpg
+ cldnn_format_os_iyx_osv32, ///< format used only for convolution weights: os - output feature maps slice, i - input feature maps, yx - spatials, sv32 - 32 values of single slice.
+ cldnn_format_os_iyx_osv64, ///< format used only for convolution weights: os - output feature maps slice, i - input feature maps, yx - spatials, sv64 - 64 values of single slice.
cldnn_format_bs_xs_xsv8_bsv8, ///< format used only for fully connected weights: bs - batch slice, xs - x slice, bsv8 - 8 values of single slice.
///< \n \image html bs_xs_xsv8_bsv8.jpg
cldnn_format_bs_xs_xsv8_bsv16,///< format used only for fully connected weights: bs - batch slice, xs - x slice, bsv16 - 16 values of single slice.
///< \n \image html image_2d_weights_c4_fyx_b.jpg
cldnn_format_image_2d_weights_c1_b_fyx, ///< image format for weights, image 2d, single channel, width size is b, height is f*y*x
///< \n \image html image_2d_weights_c1_b_fyx.jpg
- cldnn_format_byxf_af32, /// < \n format for input for primitives using MMAD
- cldnn_format_fs_bs_yx_bs4_fs32, /// < \n format for batched input for primitives using MMAD
+ cldnn_format_winograd_2x3_s1_data, ///< format used for input for winograd convolution, F(2,3) -- filter 3x3 with stride 1
+ cldnn_format_winograd_2x3_s1_weights, ///< format used for weights for winograd non-fused convolution, F(2,3) -- filter 3x3 with stride 1
+ cldnn_format_winograd_2x3_s1_fused_weights, ///< format used for weights for winograd fused convolution, F(2,3) -- filter 3x3 with stride 1
+ cldnn_format_winograd_6x3_s1_fused_weights, ///< format used for weights for winograd fused convolution, F(6,3) -- filter 3x3 with stride 1
+ cldnn_format_image_2d_weights_winograd_6x3_s1_fbxyb, ///< image format used for weights for winograd fused convolution, F(6,3) -- filter 3x3 with stride 1
+ cldnn_format_image_2d_weights_winograd_6x3_s1_xfbyb, ///< image format used for weights for winograd fused convolution, F(6,3) -- filter 3x3 with stride 1
+ cldnn_format_byxf_af32, /// < \n format for input for primitives using MMAD
+ cldnn_format_byx8_f4, /// < \n format for input for MMAD convolutions
+ cldnn_format_fs_bs_yx_bs4_fs32, /// < \n format for batched input for primitives using MMAD
cldnn_format_os_is_yx_isa8_osv8_isv4, /// < \n format for weights for MMAD convolutions, stored as ((aligned_to_8(O)/8) * (aligned_to_32(I)/32) * Y * X * ( 8 ) * ( 8 ) * ( 4 )
+ cldnn_format_os_is_yx_isa8_osv8_isv4_swizzled_by_4, /// < \n format for weights for MMAD convolutions
cldnn_format_is_o_yx_isv32, /// < \n format for weights for 1x1 MMAD convolutions
+ cldnn_format_is_o32_yx_isv32_swizzled_by_4, /// < \n format for weights for 1x1 MMAD convolutions
+ cldnn_format_os_is_y_x8_osv8_isv4, /// < n\ format for weights for MMAD convolutions
+ cldnn_bf_lyx_yx, /// < \n format for local convolution weights
+ cldnn_format_b_fs_yx_fsv4, /// < \n format for input for IMAD convolutions
+ cldnn_format_os_is_yx_osv16_isv4, /// < \n format for weights for IMAD convolutions
cldnn_format_format_num, ///< number of format types
cldnn_format_any = -1
} cldnn_format_type;
#define CLDNN_TENSOR_BATCH_DIM_MAX 1
#define CLDNN_TENSOR_FEATURE_DIM_MAX 1
#define CLDNN_TENSOR_SPATIAL_DIM_MAX 2
+#define CLDNN_TENSOR_LOCAL_DIM_MAX 2
#define CLDNN_TENSOR_DIM_MAX 8
/// @brief N-dimensional vector. Mostly used to represent memory size.
size_t batch_num;
size_t feature_num;
size_t spatial_num;
+ size_t local_num;
int32_t sizes[CLDNN_TENSOR_DIM_MAX];
} cldnn_tensor;
size_t size; ///< Size (in uint16_t) of the array.
} cldnn_uint16_t_arr;
+/// @brief Represents reference to an array of uint8_t.
+typedef struct
+{
+ const uint8_t* data; ///< Pointer to uint8_t array.
+ size_t size; ///< Size (in uint8_t) of the array.
+} cldnn_uint8_t_arr;
+
/// @brief Represents reference to an array of tensor.
typedef struct
{
size_t size; ///< Number of ids in the array.
} cldnn_primitive_id_arr;
+typedef struct
+{
+ cldnn_data_type data_type;
+ // No bool type available...
+ char enabled;
+} cldnn_optional_data_type;
+
/// @brief Custom primitive kernel source code
typedef const char* cldnn_kernel_code;
/// @brief Custom primitive kernel source code array
activation_acos, // acos(val)
activation_cosh, // cosh(val)
activation_log, // log(val)
- activation_log2, // log2(val)
+ activation_log2, // log2(val)
activation_exp, // exp(val)
+ activation_not // !(val)
} cldnn_activation_func;
/// @brief activation gradient functions
float a, b;
} cldnn_activation_additional_params;
+/// @brief Axis which index_select primitive will index.
+typedef enum index_select_axis_name_t
+{
+ along_b,
+ along_f,
+ along_y,
+ along_x
+} index_select_axis_name;
+
+/// @brief Axis which index_select primitive will index array
+typedef const index_select_axis_name* index_select_axis_name_arr;
/// @brief reorder mean operation modes
typedef enum cldnn_reorder_mean_mode_t
cldnn_primitive_type_id type; /**< @brief Primitive type identificator. */\
cldnn_primitive_id id; /**< @brief Primitive id unique within a topology. */\
cldnn_primitive_id_arr input; /**< @brief Input primitives ids. */\
- cldnn_padding output_padding; /**< @brief Output padding information. */
+ cldnn_padding output_padding; /**< @brief Output padding information. */\
+ cldnn_optional_data_type output_data_type; /**< @brief If specified, describes an explicit change of the output precision of the primitive. */
/// @brief Close primitive descriptor definition.
#define CLDNN_END_PRIMITIVE_DESC(PType) };
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