TIM-VX/src/tim/vx/internal/src/kernel/cl/clip_cl.c

304 lines
10 KiB
C

/****************************************************************************
*
* Copyright (c) 2020 Vivante Corporation
*
* Permission is hereby granted, free of charge, to any person obtaining a
* copy of this software and associated documentation files (the "Software"),
* to deal in the Software without restriction, including without limitation
* the rights to use, copy, modify, merge, publish, distribute, sublicense,
* and/or sell copies of the Software, and to permit persons to whom the
* Software is furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
* DEALINGS IN THE SOFTWARE.
*
*****************************************************************************/
#include <stdint.h>
#include <stdlib.h>
#include <string.h>
#include "vsi_nn_types.h"
#include "vsi_nn_tensor.h"
#include "vsi_nn_graph.h"
#include "vsi_nn_log.h"
#include "vsi_nn_error.h"
#include "vsi_nn_prv.h"
#include "vsi_nn_tensor_util.h"
#include "utils/vsi_nn_util.h"
#include "kernel/vsi_nn_kernel.h"
__BEGIN_DECLS
#define _CLIP_KERNEL_SOURCE(_input_type) "clip_"#_input_type
#define STR(a) #a
// Add kernel hashtable here
#define CLIP_HASH_KEY( IN_DTYPE, OUT_DTYPE, _image_2d ) \
(( IN_DTYPE << 20 ) | ( OUT_DTYPE << 8) | (_image_2d))
#define PACK_KERNEL_MAP( IN_DTYPE, OUT_DTYPE ) \
{ CLIP_HASH_KEY( IN_DTYPE, OUT_DTYPE, 0 ), \
CVIVANTE_NAMESPACE("cl.clip_"STR(IN_DTYPE)"to"STR(OUT_DTYPE)), \
_CLIP_KERNEL_SOURCE(IN_DTYPE) }
#define PACK_KERNEL_MAP_2D( IN_DTYPE, OUT_DTYPE ) \
{ CLIP_HASH_KEY( IN_DTYPE, OUT_DTYPE, 1 ), \
CVIVANTE_NAMESPACE("cl.clip_"STR(IN_DTYPE)"to"STR(OUT_DTYPE)"_2D"), \
_CLIP_KERNEL_SOURCE(IN_DTYPE) }
typedef struct
{
uint32_t key;
char * function_name;
const char * source_name;
} _kernel_map_type;
static const _kernel_map_type _clip_kernel_map[] =
{
PACK_KERNEL_MAP(F32, F32),
PACK_KERNEL_MAP(F32, U8),
PACK_KERNEL_MAP(U8, U8),
PACK_KERNEL_MAP(U8, F32),
PACK_KERNEL_MAP_2D(F32, F32),
PACK_KERNEL_MAP_2D(F32, U8),
PACK_KERNEL_MAP_2D(U8, U8),
PACK_KERNEL_MAP_2D(U8, F32),
};
/*
* Kernel params
*/
static vx_param_description_t _clip_kernel_param_def[] =
{
{VX_INPUT, VX_TYPE_TENSOR, VX_PARAMETER_STATE_REQUIRED},
{VX_OUTPUT, VX_TYPE_TENSOR, VX_PARAMETER_STATE_REQUIRED},
{VX_INPUT, VX_TYPE_SCALAR, VX_PARAMETER_STATE_REQUIRED},
{VX_INPUT, VX_TYPE_SCALAR, VX_PARAMETER_STATE_REQUIRED},
{VX_INPUT, VX_TYPE_SCALAR, VX_PARAMETER_STATE_REQUIRED},
{VX_INPUT, VX_TYPE_SCALAR, VX_PARAMETER_STATE_REQUIRED},
{VX_INPUT, VX_TYPE_SCALAR, VX_PARAMETER_STATE_REQUIRED},
{VX_INPUT, VX_TYPE_SCALAR, VX_PARAMETER_STATE_REQUIRED},
};
#define _CLIP_PARAM_NUM _cnt_of_array( _clip_kernel_param_def )
#define SCALAR_MIN_VALUE (2)
#define SCALAR_MAX_VALUE (3)
#define SCALAR_INPUT_SCALE (4)
#define SCALAR_INPUT_TAIL (5)
#define SCALAR_OUTPUT_SCALE (6)
#define SCALAR_OUTPUT_TAIL (7)
#define CLIP_PARAM_NUM 4
#define CLIP_QUANT_PARAM_NUM _cnt_of_array( _clip_kernel_param_def )
/*
* Kernel initializer
*/
DEF_KERNEL_INITIALIZER(_clip_initializer)
(
vsi_nn_kernel_node_t node,
const vsi_nn_kernel_node_param_t * param,
size_t param_size
)
{
vsi_status status = VSI_FAILURE;
gpu_param_t gpu_param = {
3,
{0, 0, 0},
{0, 0, 0},
{0, 0, 0},
{0, 0, 0}
};
vsi_nn_kernel_tensor_attr_t * output_attr = NULL;
vsi_int_array_t * out_shape = NULL;
output_attr = vsi_nn_kernel_tensor_attr_create( (vsi_nn_kernel_tensor_t)param[1] );
CHECK_PTR_FAIL_GOTO( output_attr, "Create tensor attr buffer fail.", final );
out_shape = output_attr->shape;
gpu_param.global_scale[0] = 1;
gpu_param.global_scale[1] = 1;
gpu_param.global_scale[2] = 1;
gpu_param.dim = (out_shape->size < 3 || 1 == out_shape->data[2]) ? 2 : 3;
gpu_param.global_size[0] = gpu_align_p2(
(out_shape->data[0] + gpu_param.global_scale[0] - 1)
/ gpu_param.global_scale[0], 4);
gpu_param.global_size[1] = (
(out_shape->data[1] + gpu_param.global_scale[1] - 1)
/ gpu_param.global_scale[1]);
gpu_param.global_size[2] = out_shape->size > 2 ? out_shape->data[2] : 1;
status = vsi_nn_kernel_gpu_config( node, &gpu_param );
final:
#define SAFE_FREE_TENSOR_ATTR(_PTR) if( _PTR ) { vsi_nn_kernel_tensor_attr_release( &_PTR ); _PTR = NULL; }
SAFE_FREE_TENSOR_ATTR(output_attr);
return status;
} /* _clip_initializer() */
/*
* Query kernel
*/
static vsi_status _query_kernel
(
vsi_nn_kernel_t * kernel,
vsi_nn_tensor_t * const * const inputs,
vsi_nn_tensor_t * const * const outputs,
vsi_bool image_2d,
vsi_bool *is_use_u8_kernel
)
{
vsi_status status = VSI_FAILURE;
vsi_nn_kernel_dtype_e in_dtype;
vsi_nn_kernel_dtype_e out_dtype;
const _kernel_map_type * kernel_map = _clip_kernel_map;
size_t kernel_map_size = _cnt_of_array( _clip_kernel_map );
vx_param_description_t * param_def = _clip_kernel_param_def;
size_t param_def_size = _cnt_of_array( _clip_kernel_param_def );
vx_kernel_initialize_f initializer = _clip_initializer;
uint32_t key;
uint32_t i;
in_dtype = vsi_nn_kernel_map_dtype( inputs[0]->attr.dtype.vx_type );
out_dtype = vsi_nn_kernel_map_dtype( outputs[0]->attr.dtype.vx_type );
if (F16 == in_dtype)
{
in_dtype = F32;
}
if (F16 == out_dtype)
{
out_dtype = F32;
}
if ((U8 == in_dtype) || (U8 == out_dtype))
{
param_def_size = CLIP_QUANT_PARAM_NUM;
*is_use_u8_kernel = TRUE;
}
else
{
param_def_size = CLIP_PARAM_NUM;
*is_use_u8_kernel = FALSE;
}
key = CLIP_HASH_KEY( in_dtype, out_dtype, image_2d );
for( i = 0; i < (uint32_t)kernel_map_size; i ++ )
{
if( kernel_map[i].key == key )
{
break;
}
}
if( i < (uint32_t)kernel_map_size )
{
snprintf( kernel->info.name, VX_MAX_KERNEL_NAME, "%s", kernel_map[i].function_name );
kernel->info.parameters = param_def;
kernel->info.numParams = (uint32_t)param_def_size;
kernel->info.initialize = initializer;
// Register code source
vsi_nn_kernel_add_source( kernel, VSI_NN_GPU_SOURCE_FMT_CODE, 1,
kernel_map[i].source_name );
// Register binary source
vsi_nn_kernel_add_source( kernel, VSI_NN_GPU_SOURCE_FMT_EXECUTABLE, 1,
kernel_map[i].source_name );
status = VSI_SUCCESS;
}
return status;
} /* _query_kernel() */
static vsi_nn_kernel_node_t _setup
(
vsi_nn_graph_t * graph,
vsi_nn_tensor_t ** inputs,
size_t input_num,
vsi_nn_tensor_t ** outputs,
size_t output_num,
const vsi_nn_kernel_param_t * params,
vsi_nn_kernel_t * kernel
)
{
vsi_status status = VSI_FAILURE;
vsi_nn_kernel_node_param_t node_params[_CLIP_PARAM_NUM] = {NULL};
vsi_nn_kernel_node_t node = NULL;
vsi_bool image_2d = FALSE;
float outputScale = outputs[0]->attr.dtype.scale == 0.0f ? 1.0f : outputs[0]->attr.dtype.scale;
float outputTail = (float)outputs[0]->attr.dtype.zero_point;
float inputScale = inputs[0]->attr.dtype.scale == 0.0f ? 1.0f : inputs[0]->attr.dtype.scale;
float inputTail = (float)inputs[0]->attr.dtype.zero_point;
vsi_bool is_use_u8_kernel = FALSE;
float min_value = vsi_nn_kernel_param_get_float32( params, "min_value" );
float max_value = vsi_nn_kernel_param_get_float32( params, "max_value" );
outputScale = 1.0f / outputScale;
inputTail = -(inputTail * inputScale);
if( !vsi_nn_kernel_gpu_check_shape( (int32_t*)inputs[0]->attr.size,
inputs[0]->attr.dim_num ) )
{
return NULL;
}
image_2d = (inputs[0]->attr.dim_num == 2 || inputs[0]->attr.size[2] == 1);
status = _query_kernel( kernel, inputs, outputs, image_2d, &is_use_u8_kernel);
if( VSI_SUCCESS == status)
{
size_t node_params_num = CLIP_PARAM_NUM;
node = vsi_nn_kernel_create_node( graph, kernel );
if( node )
{
/* Set inputs and outputs */
vsi_nn_kernel_node_pack_io( node_params, _CLIP_PARAM_NUM,
inputs, input_num, outputs, output_num );
node_params[SCALAR_MIN_VALUE] = vsi_nn_kernel_scalar_create( graph, F32, &min_value );
node_params[SCALAR_MAX_VALUE] = vsi_nn_kernel_scalar_create( graph, F32, &max_value );
if (is_use_u8_kernel)
{
node_params[SCALAR_INPUT_SCALE] = vsi_nn_kernel_scalar_create( graph, F32, &inputScale );
node_params[SCALAR_INPUT_TAIL] = vsi_nn_kernel_scalar_create(graph, F32, &inputTail );
node_params[SCALAR_OUTPUT_SCALE] = vsi_nn_kernel_scalar_create( graph, F32, &outputScale );
node_params[SCALAR_OUTPUT_TAIL] = vsi_nn_kernel_scalar_create(graph, F32, &outputTail );
node_params_num = CLIP_QUANT_PARAM_NUM;
}
/* Pass parameters to node. */
status = vsi_nn_kernel_node_pass_param( node, node_params, node_params_num );
VSI_ASSERT( status == VSI_SUCCESS );
vsi_nn_kernel_scalar_release( &node_params[SCALAR_MIN_VALUE] );
vsi_nn_kernel_scalar_release( &node_params[SCALAR_MAX_VALUE] );
if (is_use_u8_kernel)
{
vsi_nn_kernel_scalar_release( &node_params[SCALAR_INPUT_SCALE] );
vsi_nn_kernel_scalar_release( &node_params[SCALAR_INPUT_TAIL] );
vsi_nn_kernel_scalar_release( &node_params[SCALAR_OUTPUT_SCALE] );
vsi_nn_kernel_scalar_release( &node_params[SCALAR_OUTPUT_TAIL] );
}
}
}
return node;
} /* _setup() */
__END_DECLS
REGISTER_BACKEND_CL( clip, _setup )