blob: 870e80ee9a52b31b61d05f2ef5f1c8b82a2fe9f8 [file] [log] [blame]
/*
* Copyright (c) 2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* 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.
*/
#ifndef CKW_VALIDATION_TESTS_CLKERNELWRITEROPLOADSTORETEST_H
#define CKW_VALIDATION_TESTS_CLKERNELWRITEROPLOADSTORETEST_H
#include "ckw/TileInfo.h"
#include "ckw/types/DataType.h"
#include "src/cl/CLKernelWriter.h"
#include "validation/tests/common/KernelWriterInterceptor.h"
#include "validation/tests/common/Common.h"
#include "ckw/TensorSampler.h"
#include "ckw/types/MemoryOperation.h"
#include "ckw/types/TensorSamplerTypes.h"
#include <vector>
namespace ckw
{
class CLKernelWriterOpLoadStoreTest : public ITest
{
private:
using AddressModeX = TensorSamplerAddressModeX;
using AddressModeY = TensorSamplerAddressModeY;
using AddressModeZ = TensorSamplerAddressModeZ;
using Format = TensorSamplerFormat;
using Storage = TensorStorageType;
struct Coordinates
{
Coordinates(std::string x, std::string y, std::string z, std::string batch)
: x(x), y(y), z(z), batch(batch)
{
}
std::string x;
std::string y;
std::string z;
std::string batch;
};
struct SamplerData
{
SamplerData(Format format, AddressModeX mode_x, AddressModeY mode_y, AddressModeZ mode_z)
: format(format), mode_x(mode_x), mode_y(mode_y), mode_z(mode_z)
{
}
Format format;
AddressModeX mode_x;
AddressModeY mode_y;
AddressModeZ mode_z;
};
struct Dilations
{
Dilations(std::string dilation_x, std::string dilation_y)
: dilation_x(dilation_x), dilation_y(dilation_y)
{
}
std::string dilation_x;
std::string dilation_y;
};
using CLKernelWriterOpLoadStoreConfig = std::tuple<MemoryOperation, TileInfo, TensorStorageType, SamplerData, Coordinates, Dilations, std::string>;
public:
CLKernelWriterOpLoadStoreTest()
{
// Cases
const std::string load_fp_2x3_tile = R"_(
G0__tile__0 = vload3(0, (__global float*)(G0__tensor_ptr + (G0__x) * sizeof(float) + (G0__y + 0) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (G0__b) * G0__tensor_stride3));
G0__tile__1 = vload3(0, (__global float*)(G0__tensor_ptr + (G0__x) * sizeof(float) + (G0__y + 1) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (G0__b) * G0__tensor_stride3));
)_";
const std::string load_half_2x4_tile_image_clamp_y = R"_(
G0__tile__0 = read_imageh(G0__tensor_img2d, CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST, (int2)((G0__x) >> 2, (G0__y + 0 + (G0__z) * G0__tensor_dim1 + (G0__b) * G0__tensor_dim1 * G0__tensor_dim2)));
G0__tile__1 = read_imageh(G0__tensor_img2d, CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST, (int2)((G0__x) >> 2, (G0__y + 1 + (G0__z) * G0__tensor_dim1 + (G0__b) * G0__tensor_dim1 * G0__tensor_dim2)));
)_";
const std::string store_fp_2x3_tile = R"_(
vstore3(G0__tile__0, 0, (__global float*)(G0__tensor_ptr + (G0__x) * sizeof(float) + (G0__y + 0) * G0__tensor_stride1 + (G0__b) * G0__tensor_stride3));
vstore3(G0__tile__1, 0, (__global float*)(G0__tensor_ptr + (G0__x) * sizeof(float) + (G0__y + 1) * G0__tensor_stride1 + (G0__b) * G0__tensor_stride3));
)_";
const std::string store_int8_4x4_y_dilation_batch_eq_0 = R"_(
vstore4(G0__tile__0, 0, (__global char*)(G0__tensor_ptr + (((int)(1))) * sizeof(char) + (G0__y + 0 * G0__y_dilation) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (((int)(0))) * G0__tensor_stride3));
vstore4(G0__tile__1, 0, (__global char*)(G0__tensor_ptr + (((int)(1))) * sizeof(char) + (G0__y + 1 * G0__y_dilation) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (((int)(0))) * G0__tensor_stride3));
vstore4(G0__tile__2, 0, (__global char*)(G0__tensor_ptr + (((int)(1))) * sizeof(char) + (G0__y + 2 * G0__y_dilation) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (((int)(0))) * G0__tensor_stride3));
vstore4(G0__tile__3, 0, (__global char*)(G0__tensor_ptr + (((int)(1))) * sizeof(char) + (G0__y + 3 * G0__y_dilation) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (((int)(0))) * G0__tensor_stride3));
)_";
// tensor dimension is 10
const std::string load_fp_2x3_tile_x_overlapping_min_y_eq_0_batch_eq_1 = R"_(
if(G0__x > 0)
{
G0__tile__0 = vload3(0, (__global float*)(G0__tensor_ptr + (G0__x) * sizeof(float) + (((int)(0)) + 0) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (((int)(1))) * G0__tensor_stride3));
G0__tile__1 = vload3(0, (__global float*)(G0__tensor_ptr + (G0__x) * sizeof(float) + (((int)(0)) + 1) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (((int)(1))) * G0__tensor_stride3));
}
else
{
G0__tile__0.s0 = *((__global float*)(G0__tensor_ptr + (G0__x + 0) * sizeof(float) + (((int)(0)) + 0) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (((int)(1))) * G0__tensor_stride3));
G0__tile__1.s0 = *((__global float*)(G0__tensor_ptr + (G0__x + 0) * sizeof(float) + (((int)(0)) + 1) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (((int)(1))) * G0__tensor_stride3));
}
)_";
const std::string store_fp_2x3_tile_x_overlapping_min_y_clamp_to_border_max_only = R"_(
if(G0__x > 0)
{
if(G0__y + 0 < G0__tensor_dim1)
{
vstore3(G0__tile__0, 0, (__global float*)(G0__tensor_ptr + (G0__x) * sizeof(float) + (G0__y + 0) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (G0__b) * G0__tensor_stride3));
}
else
{
G0__tile__0 = 0.0f;
}
if(G0__y + 1 < G0__tensor_dim1)
{
vstore3(G0__tile__1, 0, (__global float*)(G0__tensor_ptr + (G0__x) * sizeof(float) + (G0__y + 1) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (G0__b) * G0__tensor_stride3));
}
else
{
G0__tile__1 = 0.0f;
}
}
else
{
if(G0__y + 0 < G0__tensor_dim1)
{
*((__global float*)(G0__tensor_ptr + (G0__x + 0) * sizeof(float) + (G0__y + 0) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (G0__b) * G0__tensor_stride3)) = G0__tile__0.s0;
}
else
{
G0__tile__0.s0 = 0.0f;
}
if(G0__y + 1 < G0__tensor_dim1)
{
*((__global float*)(G0__tensor_ptr + (G0__x + 0) * sizeof(float) + (G0__y + 1) * G0__tensor_stride1 + (G0__z) * G0__tensor_stride2 + (G0__b) * G0__tensor_stride3)) = G0__tile__1.s0;
}
else
{
G0__tile__1.s0 = 0.0f;
}
}
)_";
const std::string store_half_2x4_tile_x_image_y_dilation = R"_(
write_imageh(G0__tensor_img2d, (int2)((G0__x) >> 2, (((int)(0)) + 0 * G0__y_dilation + (G0__z) * G0__tensor_dim1 + (((int)(1))) * G0__tensor_dim1 * G0__tensor_dim2)), G0__tile__0);
write_imageh(G0__tensor_img2d, (int2)((G0__x) >> 2, (((int)(0)) + 1 * G0__y_dilation + (G0__z) * G0__tensor_dim1 + (((int)(1))) * G0__tensor_dim1 * G0__tensor_dim2)), G0__tile__1);
)_";
// Configs Bundled
_configs = {
// op, tile, storage, sampler, coordinates, dilation, expected
{
MemoryOperation::Load,
TileInfo(DataType::Fp32, 2, 3),
TensorStorageType::BufferUint8Ptr,
SamplerData(Format::Dim0_Dim1_Dim2, AddressModeX::None, AddressModeY::None, AddressModeZ::None),
Coordinates("x", "y", "z", "b"),
Dilations("1", "1"),
load_fp_2x3_tile
},
{
MemoryOperation::Load,
TileInfo(DataType::Fp16, 2, 4),
TensorStorageType::Texture2dReadOnly,
SamplerData(Format::Dim0_Dim1_Dim2, AddressModeX::None, AddressModeY::ClampToBorderMaxOnly, AddressModeZ::None),
Coordinates("x", "y", "z", "b"),
Dilations("1", "1"),
load_half_2x4_tile_image_clamp_y
},
{
MemoryOperation::Store,
TileInfo(DataType::Fp32, 2, 3),
TensorStorageType::BufferUint8Ptr,
SamplerData(Format::Dim0_Dim1xDim2_1,AddressModeX::None, AddressModeY::None, AddressModeZ::None),
Coordinates("x", "y", "z", "b"),
Dilations("1", "1"),
store_fp_2x3_tile
},
{
MemoryOperation::Store,
TileInfo(DataType::Int8, 4, 4),
TensorStorageType::BufferUint8Ptr,
SamplerData(Format::Dim0_Dim1_Dim2, AddressModeX::None, AddressModeY::None, AddressModeZ::None),
Coordinates("1", "y", "z", "0"),
Dilations("1", "y_dilation"),
store_int8_4x4_y_dilation_batch_eq_0
},
{
MemoryOperation::Load,
TileInfo(DataType::Fp32, 2, 3),
TensorStorageType::BufferUint8Ptr,
SamplerData(Format::Dim0_Dim1_Dim2, AddressModeX::OverlappingMin, AddressModeY::None, AddressModeZ::None),
Coordinates("x", "0", "z", "1"),
Dilations("1", "1"),
load_fp_2x3_tile_x_overlapping_min_y_eq_0_batch_eq_1
},
{
MemoryOperation::Store,
TileInfo(DataType::Fp32, 2, 3),
TensorStorageType::BufferUint8Ptr,
SamplerData(Format::Dim0_Dim1_Dim2, AddressModeX::OverlappingMin, AddressModeY::ClampToBorderMaxOnly, AddressModeZ::None),
Coordinates("x", "y", "z", "b"),
Dilations("1", "1"),
store_fp_2x3_tile_x_overlapping_min_y_clamp_to_border_max_only
},
{
MemoryOperation::Store,
TileInfo(DataType::Fp16, 2, 4),
TensorStorageType::Texture2dWriteOnly,
SamplerData(Format::Dim0_Dim1_Dim2, AddressModeX::None, AddressModeY::None, AddressModeZ::None),
Coordinates("x", "0", "z", "1"),
Dilations("1", "y_dilation"),
store_half_2x4_tile_x_image_y_dilation
}
};
}
TileOperand declare_tile_helper(KernelWriter &writer, std::string tile)
{
if(tile == "0" || tile == "1")
{
return writer.declare_constant_tile(ConstantData({{std::stoi(tile)}}, DataType::Int32));
}
else
{
return writer.declare_tile(tile, TileInfo(DataType::Int32));
}
}
bool run() override
{
bool all_tests_passed = true;
int32_t test_idx = 0;
for(auto _config: _configs)
{
KernelWriterInterceptor<CLKernelWriter> writer;
const MemoryOperation op = std::get<0>(_config);
const TileInfo tile_info = std::get<1>(_config);
const Storage storage = std::get<2>(_config);
const SamplerData sampler_data = std::get<3>(_config);
const Coordinates coord = std::get<4>(_config);
const Dilations dilations = std::get<5>(_config);
const std::string expected_code = std::get<6>(_config).substr(1); // ignore initial newline, which was added for convenience
TileOperand tile_op = writer.declare_tile("tile", tile_info);
TileOperand x_op = declare_tile_helper(writer, coord.x);
TileOperand y_op = declare_tile_helper(writer, coord.y);
TileOperand z_op = declare_tile_helper(writer, coord.z);
TileOperand batch_op = declare_tile_helper(writer, coord.batch);
TileOperand dil_x_op = declare_tile_helper(writer, dilations.dilation_x);
TileOperand dil_y_op = declare_tile_helper(writer, dilations.dilation_y);
TensorShape tensor_shape {10, 10, 10, 10};
TensorInfo tensor_info(tile_info.data_type(), tensor_shape, TensorDataLayout::Nhwc, 0 /* id */);
TensorOperand tensor_op = writer.declare_tensor_argument("tensor", tensor_info);
TensorSampler sampler(storage, sampler_data.format, sampler_data.mode_x, sampler_data.mode_y, sampler_data.mode_z);
const bool no_dilation = (dilations.dilation_x == "1" && dilations.dilation_y == "1");
writer.start_capture_code();
if(op == MemoryOperation::Load)
{
if(no_dilation)
{
writer.op_load(tile_op, tensor_op, sampler, x_op, y_op, z_op, batch_op);
}
else
{
writer.op_load_dilated(tile_op, tensor_op, sampler, x_op, y_op, z_op, batch_op, dil_x_op, dil_y_op);
}
}
else
{
if(no_dilation)
{
writer.op_store(tensor_op, tile_op, sampler, x_op, y_op, z_op, batch_op);
}
else
{
writer.op_store_dilated(tensor_op, tile_op, sampler, x_op, y_op, z_op, batch_op, dil_x_op, dil_y_op);
}
}
VALIDATE_TEST(writer.check_added_code(expected_code), all_tests_passed, test_idx++);
}
return all_tests_passed;
}
std::string name() override
{
return "CLKernelWriterOpLoadStoreTest";
}
private:
std::vector<CLKernelWriterOpLoadStoreConfig> _configs {};
};
} // namespace ckw
#endif // CKW_VALIDATION_TESTS_CLKERNELWRITEROPLOADSTORETEST_H