| // |
| // Copyright (c) 2017 The Khronos Group Inc. |
| // |
| // Licensed under the Apache License, Version 2.0 (the "License"); |
| // you may not use this file except in compliance with the License. |
| // You may obtain a copy of the License at |
| // |
| // http://www.apache.org/licenses/LICENSE-2.0 |
| // |
| // Unless required by applicable law or agreed to in writing, software |
| // distributed under the License is distributed on an "AS IS" BASIS, |
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| // See the License for the specific language governing permissions and |
| // limitations under the License. |
| // |
| #include "test_common.h" |
| #include <float.h> |
| |
| extern cl_mem_flags gMemFlagsToUse; |
| extern int gtestTypesToRun; |
| |
| // Utility function to clamp down image sizes for certain tests to avoid |
| // using too much memory. |
| static size_t reduceImageSizeRange(size_t maxDimSize) { |
| size_t DimSize = maxDimSize/128; |
| if (DimSize < (size_t) 16) |
| return 16; |
| else if (DimSize > (size_t) 64) |
| return 64; |
| else |
| return DimSize; |
| } |
| |
| static size_t reduceImageDepth(size_t maxDepth) { |
| size_t Depth = maxDepth/32; |
| if (Depth < (size_t) 8) |
| return 8; |
| else if (Depth > (size_t) 32) |
| return 32; |
| else |
| return Depth; |
| } |
| |
| const char *read2DArrayKernelSourcePattern = |
| "__kernel void sample_kernel( read_only %s input,%s __global float *xOffsets, __global float *yOffsets, __global float *zOffsets, __global %s%s *results %s )\n" |
| "{\n" |
| "%s" |
| " int tidX = get_global_id(0), tidY = get_global_id(1), tidZ = get_global_id(2);\n" |
| "%s" |
| "%s" |
| " results[offset] = read_image%s( input, imageSampler, coords %s);\n" |
| "}"; |
| |
| const char *read_write2DArrayKernelSourcePattern = |
| "__kernel void sample_kernel( read_write %s input,%s __global float *xOffsets, __global float *yOffsets, __global float *zOffsets, __global %s%s *results %s)\n" |
| "{\n" |
| "%s" |
| " int tidX = get_global_id(0), tidY = get_global_id(1), tidZ = get_global_id(2);\n" |
| "%s" |
| "%s" |
| " results[offset] = read_image%s( input, coords %s);\n" |
| "}"; |
| |
| const char* offset2DarraySource =" int offset = tidZ*get_image_width(input)*get_image_height(input) + tidY*get_image_width(input) + tidX;\n"; |
| const char* offset2DarraySourceLod = |
| " int lod_int = (int)lod;\n" |
| " int width_lod, height_lod;\n" |
| " width_lod = (get_image_width(input) >> lod_int ) ? (get_image_width(input) >> lod_int ) : 1;\n" |
| " height_lod = (get_image_height(input) >> lod_int ) ? (get_image_height(input) >> lod_int ) : 1;\n" |
| " int offset = tidZ*width_lod*height_lod + tidY*width_lod + tidX;\n"; |
| |
| const char *int2DArrayCoordKernelSource = |
| " int4 coords = (int4)( (int) xOffsets[offset], (int) yOffsets[offset], (int) zOffsets[offset], 0 );\n"; |
| |
| const char *float2DArrayUnnormalizedCoordKernelSource = |
| " float4 coords = (float4)( xOffsets[offset], yOffsets[offset], zOffsets[offset], 0.0f );\n"; |
| |
| |
| static const char *samplerKernelArg = " sampler_t imageSampler,"; |
| |
| extern void read_image_pixel_float( void *imageData, image_descriptor *imageInfo, int x, int y, int z, float *outData ); |
| template <class T> int determine_validation_error_offset_2D_array( void *imagePtr, image_descriptor *imageInfo, image_sampler_data *imageSampler, |
| T *resultPtr, T * expected, float error, |
| float x, float y, float z, float xAddressOffset, float yAddressOffset, float zAddressOffset, size_t j, int &numTries, int &numClamped, bool printAsFloat, int lod ) |
| { |
| int actualX, actualY, actualZ; |
| int found = debug_find_pixel_in_image( imagePtr, imageInfo, resultPtr, &actualX, &actualY, &actualZ, lod ); |
| bool clampingErr = false, clamped = false, otherClampingBug = false; |
| int clampedX, clampedY, clampedZ; |
| |
| size_t imageWidth = imageInfo->width, imageHeight = imageInfo->height, imageDepth = imageInfo->arraySize; |
| |
| clamped = get_integer_coords_offset( x, y, z, xAddressOffset, yAddressOffset, zAddressOffset, imageWidth, imageHeight, imageDepth, imageSampler, imageInfo, clampedX, clampedY, clampedZ ); |
| |
| if( found ) |
| { |
| // Is it a clamping bug? |
| if( clamped && clampedX == actualX && clampedY == actualY && clampedZ == actualZ ) |
| { |
| if( (--numClamped) == 0 ) |
| { |
| log_error( "\nERROR: TEST FAILED! Read is erroneously clamping coordinates!\n" ); |
| if( printAsFloat ) |
| { |
| log_error( "Sample %ld: coord {%f(%a),%f(%a),%f(%a)} did not validate!\n" |
| " Expected (%g,%g,%g,%g)\n" |
| " Observed (%g,%g,%g,%g)\n" |
| " error of %g\n", |
| j, x, x, y, y, z, z, (float)expected[ 0 ], (float)expected[ 1 ], (float)expected[ 2 ], (float)expected[ 3 ], |
| (float)resultPtr[ 0 ], (float)resultPtr[ 1 ], (float)resultPtr[ 2 ], (float)resultPtr[ 3 ], error ); |
| } |
| else |
| { |
| log_error( "Sample %ld: coord {%f(%a),%f(%a),%f(%a)} did not validate!\n" |
| " Expected (%x,%x,%x,%x)\n" |
| " Observed (%x,%x,%x,%x)\n", |
| j, x, x, y, y, z, z, (int)expected[ 0 ], (int)expected[ 1 ], (int)expected[ 2 ], (int)expected[ 3 ], |
| (int)resultPtr[ 0 ], (int)resultPtr[ 1 ], (int)resultPtr[ 2 ], (int)resultPtr[ 3 ] ); |
| } |
| |
| if( imageSampler->filter_mode != CL_FILTER_LINEAR ) |
| { |
| if( found ) |
| log_error( "\tValue really found in image at %d,%d,%d (%s)\n", actualX, actualY, actualZ, ( found > 1 ) ? "NOT unique!!" : "unique" ); |
| else |
| log_error( "\tValue not actually found in image\n" ); |
| } |
| log_error( "\n" ); |
| |
| return -1; |
| } |
| clampingErr = true; |
| otherClampingBug = true; |
| } |
| } |
| if( clamped && !otherClampingBug ) |
| { |
| // If we are in clamp-to-edge mode and we're getting zeroes, it's possible we're getting border erroneously |
| if( resultPtr[ 0 ] == 0 && resultPtr[ 1 ] == 0 && resultPtr[ 2 ] == 0 && resultPtr[ 3 ] == 0 ) |
| { |
| if( (--numClamped) == 0 ) |
| { |
| log_error( "\nERROR: TEST FAILED: Clamping is erroneously returning border color!\n" ); |
| if( printAsFloat ) |
| { |
| log_error( "Sample %ld: coord {%f(%a),%f(%a),%f(%a)} did not validate!\n" |
| " Expected (%g,%g,%g,%g)\n" |
| " Observed (%g,%g,%g,%g)\n" |
| " error of %g\n", |
| j, x, x, y, y, z, z, (float)expected[ 0 ], (float)expected[ 1 ], (float)expected[ 2 ], (float)expected[ 3 ], |
| (float)resultPtr[ 0 ], (float)resultPtr[ 1 ], (float)resultPtr[ 2 ], (float)resultPtr[ 3 ], error ); |
| } |
| else |
| { |
| log_error( "Sample %ld: coord {%f(%a),%f(%a),%f(%a)} did not validate!\n" |
| " Expected (%x,%x,%x,%x)\n" |
| " Observed (%x,%x,%x,%x)\n", |
| j, x, x, y, y, z, z, (int)expected[ 0 ], (int)expected[ 1 ], (int)expected[ 2 ], (int)expected[ 3 ], |
| (int)resultPtr[ 0 ], (int)resultPtr[ 1 ], (int)resultPtr[ 2 ], (int)resultPtr[ 3 ] ); |
| } |
| return -1; |
| } |
| clampingErr = true; |
| } |
| } |
| if( !clampingErr ) |
| { |
| if( true ) // gExtraValidateInfo ) |
| { |
| if( printAsFloat ) |
| { |
| log_error( "Sample %ld: coord {%f(%a),%f(%a),%f(%a)} did not validate!\n" |
| " Expected (%g,%g,%g,%g)\n" |
| " Observed (%g,%g,%g,%g)\n" |
| " error of %g\n", |
| j, x, x, y, y, z, z, (float)expected[ 0 ], (float)expected[ 1 ], (float)expected[ 2 ], (float)expected[ 3 ], |
| (float)resultPtr[ 0 ], (float)resultPtr[ 1 ], (float)resultPtr[ 2 ], (float)resultPtr[ 3 ], error ); |
| } |
| else |
| { |
| log_error( "Sample %ld: coord {%f(%a),%f(%a),%f(%a)} did not validate!\n" |
| " Expected (%x,%x,%x,%x)\n" |
| " Observed (%x,%x,%x,%x)\n", |
| j, x, x, y, y, z, z, (int)expected[ 0 ], (int)expected[ 1 ], (int)expected[ 2 ], (int)expected[ 3 ], |
| (int)resultPtr[ 0 ], (int)resultPtr[ 1 ], (int)resultPtr[ 2 ], (int)resultPtr[ 3 ] ); |
| } |
| log_error( "Integer coords resolve to %d,%d,%d, image size = %d,%d,%d\n", clampedX, clampedY, clampedZ, (int)imageWidth, (int)imageHeight, (int)imageDepth ); |
| |
| if( printAsFloat && gExtraValidateInfo ) |
| { |
| log_error( "\nNearby values:\n" ); |
| for( int zOff = -1; zOff <= 1; zOff++ ) |
| { |
| for( int yOff = -1; yOff <= 1; yOff++ ) |
| { |
| float top[ 4 ], real[ 4 ], bot[ 4 ]; |
| read_image_pixel_float( imagePtr, imageInfo, clampedX - 1 , clampedY + yOff, clampedZ + zOff, top ); |
| read_image_pixel_float( imagePtr, imageInfo, clampedX ,clampedY + yOff, clampedZ + zOff, real ); |
| read_image_pixel_float( imagePtr, imageInfo, clampedX + 1, clampedY + yOff, clampedZ + zOff, bot ); |
| log_error( "\t(%g,%g,%g,%g)",top[0], top[1], top[2], top[3] ); |
| log_error( " (%g,%g,%g,%g)", real[0], real[1], real[2], real[3] ); |
| log_error( " (%g,%g,%g,%g)\n",bot[0], bot[1], bot[2], bot[3] ); |
| } |
| } |
| } |
| if( imageSampler->filter_mode != CL_FILTER_LINEAR ) |
| { |
| if( found ) |
| log_error( "Value really found in image at %d,%d,%d (%s)\n", actualX, actualY, actualZ, ( found > 1 ) ? "NOT unique!!" : "unique" ); |
| else |
| log_error( "Value not actually found in image\n" ); |
| } |
| log_error( "\n" ); |
| } |
| |
| numClamped = -1; // We force the clamped counter to never work |
| if( ( --numTries ) == 0 ) |
| return -1; |
| } |
| return 0; |
| } |
| |
| static void InitFloatCoords( image_descriptor *imageInfo, image_sampler_data *imageSampler, float *xOffsets, float *yOffsets, float *zOffsets, float xfract, float yfract, float zfract, int normalized_coords, MTdata d , int lod) |
| { |
| size_t i = 0; |
| size_t width_lod = imageInfo->width; |
| size_t height_lod = imageInfo->height; |
| if(gTestMipmaps) |
| { |
| width_lod = ( imageInfo->width >> lod) ?( imageInfo->width >> lod) : 1; |
| height_lod = ( imageInfo->height >> lod) ?( imageInfo->height >> lod) : 1; |
| |
| } |
| if( gDisableOffsets ) |
| { |
| for( size_t z = 0; z < imageInfo->arraySize; z++ ) |
| { |
| for( size_t y = 0; y < height_lod; y++ ) |
| { |
| for( size_t x = 0; x < width_lod; x++, i++ ) |
| { |
| xOffsets[ i ] = (float) (xfract + (double) x); |
| yOffsets[ i ] = (float) (yfract + (double) y); |
| zOffsets[ i ] = (float) (zfract + (double) z); |
| } |
| } |
| } |
| } |
| else |
| { |
| for( size_t z = 0; z < imageInfo->arraySize; z++ ) |
| { |
| for( size_t y = 0; y < height_lod; y++ ) |
| { |
| for( size_t x = 0; x < width_lod; x++, i++ ) |
| { |
| xOffsets[ i ] = (float) (xfract + (double) ((int) x + random_in_range( -10, 10, d ))); |
| yOffsets[ i ] = (float) (yfract + (double) ((int) y + random_in_range( -10, 10, d ))); |
| zOffsets[ i ] = (float) (zfract + (double) ((int) z + random_in_range( -10, 10, d ))); |
| } |
| } |
| } |
| } |
| |
| if( imageSampler->addressing_mode == CL_ADDRESS_NONE ) |
| { |
| i = 0; |
| for( size_t z = 0; z < imageInfo->arraySize; z++ ) |
| { |
| for( size_t y = 0; y < height_lod; y++ ) |
| { |
| for( size_t x = 0; x < width_lod; x++, i++ ) |
| { |
| xOffsets[ i ] = (float) CLAMP( (double) xOffsets[ i ], 0.0, (double) width_lod - 1.0); |
| yOffsets[ i ] = (float) CLAMP( (double) yOffsets[ i ], 0.0, (double) height_lod - 1.0); |
| zOffsets[ i ] = (float) CLAMP( (double) zOffsets[ i ], 0.0, (double) imageInfo->arraySize - 1.0); |
| } |
| } |
| } |
| } |
| |
| if( normalized_coords ) |
| { |
| i = 0; |
| for( size_t z = 0; z < imageInfo->arraySize; z++ ) |
| { |
| for( size_t y = 0; y < height_lod; y++ ) |
| { |
| for( size_t x = 0; x < width_lod; x++, i++ ) |
| { |
| xOffsets[ i ] = (float) ((double) xOffsets[ i ] / (double) width_lod); |
| yOffsets[ i ] = (float) ((double) yOffsets[ i ] / (double) height_lod); |
| } |
| } |
| } |
| } |
| } |
| |
| int test_read_image_2D_array( cl_context context, cl_command_queue queue, cl_kernel kernel, |
| image_descriptor *imageInfo, image_sampler_data *imageSampler, |
| bool useFloatCoords, ExplicitType outputType, MTdata d ) |
| { |
| int error; |
| size_t threads[3]; |
| static int initHalf = 0; |
| cl_mem_flags image_read_write_flags = CL_MEM_READ_ONLY; |
| |
| clMemWrapper xOffsets, yOffsets, zOffsets, results; |
| clSamplerWrapper actualSampler; |
| BufferOwningPtr<char> maxImageUseHostPtrBackingStore; |
| |
| // Create offset data |
| BufferOwningPtr<cl_float> xOffsetValues(malloc(sizeof(cl_float) *imageInfo->width * imageInfo->height * imageInfo->arraySize)); |
| BufferOwningPtr<cl_float> yOffsetValues(malloc(sizeof(cl_float) *imageInfo->width * imageInfo->height * imageInfo->arraySize)); |
| BufferOwningPtr<cl_float> zOffsetValues(malloc(sizeof(cl_float) *imageInfo->width * imageInfo->height * imageInfo->arraySize)); |
| |
| BufferOwningPtr<char> imageValues; |
| generate_random_image_data( imageInfo, imageValues, d ); |
| |
| // Construct testing sources |
| clProtectedImage protImage; |
| clMemWrapper unprotImage; |
| cl_mem image; |
| |
| if(gtestTypesToRun & kReadTests) |
| { |
| image_read_write_flags = CL_MEM_READ_ONLY; |
| } |
| else |
| { |
| image_read_write_flags = CL_MEM_READ_WRITE; |
| } |
| |
| if( gMemFlagsToUse == CL_MEM_USE_HOST_PTR ) |
| { |
| // clProtectedImage uses USE_HOST_PTR, so just rely on that for the testing (via Ian) |
| // Do not use protected images for max image size test since it rounds the row size to a page size |
| if (gTestMaxImages) { |
| generate_random_image_data( imageInfo, maxImageUseHostPtrBackingStore, d ); |
| unprotImage = create_image_2d_array( context, |
| image_read_write_flags | CL_MEM_USE_HOST_PTR, |
| imageInfo->format, |
| imageInfo->width, imageInfo->height, |
| imageInfo->arraySize, |
| ( gEnablePitch ? imageInfo->rowPitch : 0 ), |
| ( gEnablePitch ? imageInfo->slicePitch : 0 ), |
| maxImageUseHostPtrBackingStore, &error ); |
| } else { |
| error = protImage.Create( context, CL_MEM_OBJECT_IMAGE2D_ARRAY, |
| image_read_write_flags, |
| imageInfo->format, imageInfo->width, imageInfo->height, 1, imageInfo->arraySize ); |
| } |
| if( error != CL_SUCCESS ) |
| { |
| log_error( "ERROR: Unable to create 2D image array of size %d x %d x %d (pitch %d, %d ) (%s)", (int)imageInfo->width, (int)imageInfo->height, (int)imageInfo->arraySize, (int)imageInfo->rowPitch, (int)imageInfo->slicePitch, IGetErrorString( error ) ); |
| return error; |
| } |
| if (gTestMaxImages) |
| image = (cl_mem)unprotImage; |
| else |
| image = (cl_mem)protImage; |
| } |
| else if( gMemFlagsToUse == CL_MEM_COPY_HOST_PTR ) |
| { |
| // Don't use clEnqueueWriteImage; just use copy host ptr to get the data in |
| unprotImage = create_image_2d_array( context, |
| image_read_write_flags | CL_MEM_COPY_HOST_PTR, |
| imageInfo->format, |
| imageInfo->width, |
| imageInfo->height, |
| imageInfo->arraySize, |
| ( gEnablePitch ? imageInfo->rowPitch : 0 ), |
| ( gEnablePitch ? imageInfo->slicePitch : 0 ), |
| imageValues, &error ); |
| if( error != CL_SUCCESS ) |
| { |
| log_error( "ERROR: Unable to create 2D image array of size %d x %d x %d (pitch %d, %d ) (%s)", (int)imageInfo->width, (int)imageInfo->height, (int)imageInfo->arraySize, (int)imageInfo->rowPitch, (int)imageInfo->slicePitch, IGetErrorString( error ) ); |
| return error; |
| } |
| image = unprotImage; |
| } |
| else // Either CL_MEM_ALLOC_HOST_PTR or none |
| { |
| if ( gTestMipmaps ) |
| { |
| cl_image_desc image_desc = {0}; |
| image_desc.image_type = CL_MEM_OBJECT_IMAGE2D_ARRAY; |
| image_desc.image_width = imageInfo->width; |
| image_desc.image_height = imageInfo->height; |
| image_desc.image_array_size = imageInfo->arraySize; |
| //image_desc.image_rowPitch = imageInfo->rowPitch; |
| //image_desc.image_slicePitch = imageInfo->slicePitch; |
| image_desc.num_mip_levels = imageInfo->num_mip_levels; |
| |
| unprotImage = clCreateImage( context, |
| image_read_write_flags, |
| imageInfo->format, &image_desc, NULL, &error); |
| if( error != CL_SUCCESS ) |
| { |
| log_error( "ERROR: Unable to create %d level mipmapped 2D image array of size %d x %d x %d (pitch %d, %d ) (%s)", (int)imageInfo->num_mip_levels, (int)imageInfo->width, (int)imageInfo->height, (int)imageInfo->arraySize, (int)imageInfo->rowPitch, (int)imageInfo->slicePitch, IGetErrorString( error ) ); |
| return error; |
| } |
| } |
| else |
| { |
| // Note: if ALLOC_HOST_PTR is used, the driver allocates memory that can be accessed by the host, but otherwise |
| // it works just as if no flag is specified, so we just do the same thing either way |
| unprotImage = create_image_2d_array( context, |
| image_read_write_flags | gMemFlagsToUse, |
| imageInfo->format, |
| imageInfo->width, imageInfo->height, imageInfo->arraySize, |
| ( gEnablePitch ? imageInfo->rowPitch : 0 ), |
| ( gEnablePitch ? imageInfo->slicePitch : 0 ), |
| imageValues, &error ); |
| if( error != CL_SUCCESS ) |
| { |
| log_error( "ERROR: Unable to create 2D image array of size %d x %d x %d (pitch %d, %d ) (%s)", (int)imageInfo->width, (int)imageInfo->height, (int)imageInfo->arraySize, (int)imageInfo->rowPitch, (int)imageInfo->slicePitch, IGetErrorString( error ) ); |
| return error; |
| } |
| } |
| image = unprotImage; |
| } |
| |
| if( gMemFlagsToUse != CL_MEM_COPY_HOST_PTR ) |
| { |
| if( gDebugTrace ) |
| log_info( " - Writing image...\n" ); |
| |
| size_t origin[ 4 ] = { 0, 0, 0, 0 }; |
| size_t region[ 3 ] = { imageInfo->width, imageInfo->height, imageInfo->arraySize }; |
| size_t tmpNextLevelOffset = 0; |
| |
| if( gTestMipmaps ) |
| { |
| for(int level = 0; level < imageInfo->num_mip_levels; level++) |
| { |
| origin[3] = level; |
| error = clEnqueueWriteImage(queue, image, CL_TRUE, |
| origin, region, /*gEnablePitch ? imageInfo->rowPitch :*/ 0, /*gEnablePitch ? imageInfo->slicePitch :*/ 0, |
| imageValues + tmpNextLevelOffset, 0, NULL, NULL); |
| if (error != CL_SUCCESS) |
| { |
| log_error( "ERROR: Unable to write to level %d of 2D image array of size %d x %d x %d\n", (int)imageInfo->num_mip_levels, (int)imageInfo->width, (int)imageInfo->height, (int)imageInfo->arraySize ); |
| return error; |
| } |
| |
| tmpNextLevelOffset += region[0]*region[1]*region[2]*get_pixel_size(imageInfo->format); |
| region[0] = ( region[0] >> 1 ) ? ( region[0] >> 1 ) : 1; |
| region[1] = ( region[1] >> 1 ) ? ( region[1] >> 1 ) : 1; |
| } |
| } |
| else |
| { |
| error = clEnqueueWriteImage(queue, image, CL_TRUE, |
| origin, region, gEnablePitch ? imageInfo->rowPitch : 0, gEnablePitch ? imageInfo->slicePitch : 0, |
| imageValues, 0, NULL, NULL); |
| if (error != CL_SUCCESS) |
| { |
| log_error( "ERROR: Unable to write to 2D image array of size %d x %d x %d\n", (int)imageInfo->width, (int)imageInfo->height, (int)imageInfo->arraySize ); |
| return error; |
| } |
| } |
| } |
| |
| xOffsets = clCreateBuffer(context, CL_MEM_COPY_HOST_PTR, |
| sizeof(cl_float) * imageInfo->width |
| * imageInfo->height * imageInfo->arraySize, |
| xOffsetValues, &error); |
| test_error( error, "Unable to create x offset buffer" ); |
| yOffsets = clCreateBuffer(context, CL_MEM_COPY_HOST_PTR, |
| sizeof(cl_float) * imageInfo->width |
| * imageInfo->height * imageInfo->arraySize, |
| yOffsetValues, &error); |
| test_error( error, "Unable to create y offset buffer" ); |
| zOffsets = clCreateBuffer(context, CL_MEM_COPY_HOST_PTR, |
| sizeof(cl_float) * imageInfo->width |
| * imageInfo->height * imageInfo->arraySize, |
| zOffsetValues, &error); |
| test_error( error, "Unable to create y offset buffer" ); |
| results = |
| clCreateBuffer(context, CL_MEM_READ_WRITE, |
| get_explicit_type_size(outputType) * 4 * imageInfo->width |
| * imageInfo->height * imageInfo->arraySize, |
| NULL, &error); |
| test_error( error, "Unable to create result buffer" ); |
| |
| // Create sampler to use |
| actualSampler = create_sampler(context, imageSampler, gTestMipmaps, &error); |
| test_error(error, "Unable to create image sampler"); |
| |
| // Set arguments |
| int idx = 0; |
| error = clSetKernelArg( kernel, idx++, sizeof( cl_mem ), &image ); |
| test_error( error, "Unable to set kernel arguments" ); |
| if( !gUseKernelSamplers ) |
| { |
| error = clSetKernelArg( kernel, idx++, sizeof( cl_sampler ), &actualSampler ); |
| test_error( error, "Unable to set kernel arguments" ); |
| } |
| error = clSetKernelArg( kernel, idx++, sizeof( cl_mem ), &xOffsets ); |
| test_error( error, "Unable to set kernel arguments" ); |
| error = clSetKernelArg( kernel, idx++, sizeof( cl_mem ), &yOffsets ); |
| test_error( error, "Unable to set kernel arguments" ); |
| error = clSetKernelArg( kernel, idx++, sizeof( cl_mem ), &zOffsets ); |
| test_error( error, "Unable to set kernel arguments" ); |
| error = clSetKernelArg( kernel, idx++, sizeof( cl_mem ), &results ); |
| test_error( error, "Unable to set kernel arguments" ); |
| |
| const float float_offsets[] = { 0.0f, MAKE_HEX_FLOAT(0x1.0p-30f, 0x1L, -30), 0.25f, 0.3f, 0.5f - FLT_EPSILON/4.0f, 0.5f, 0.9f, 1.0f - FLT_EPSILON/2 }; |
| int float_offset_count = sizeof( float_offsets) / sizeof( float_offsets[0] ); |
| int numTries = MAX_TRIES, numClamped = MAX_CLAMPED; |
| int loopCount = 2 * float_offset_count; |
| if( ! useFloatCoords ) |
| loopCount = 1; |
| if (gTestMaxImages) { |
| loopCount = 1; |
| log_info("Testing each size only once with pixel offsets of %g for max sized images.\n", float_offsets[0]); |
| } |
| |
| // Get the maximum absolute error for this format |
| double formatAbsoluteError = get_max_absolute_error(imageInfo->format, imageSampler); |
| if (gDebugTrace) log_info("\tformatAbsoluteError is %e\n", formatAbsoluteError); |
| |
| if (0 == initHalf && imageInfo->format->image_channel_data_type == CL_HALF_FLOAT ) { |
| initHalf = CL_SUCCESS == DetectFloatToHalfRoundingMode( queue ); |
| if (initHalf) { |
| log_info("Half rounding mode successfully detected.\n"); |
| } |
| } |
| size_t nextLevelOffset = 0; |
| size_t width_lod = imageInfo->width, height_lod = imageInfo->height; |
| for( size_t lod = 0; (gTestMipmaps && (lod < imageInfo->num_mip_levels))|| (!gTestMipmaps && lod < 1); lod ++) |
| { |
| size_t resultValuesSize = width_lod * height_lod * imageInfo->arraySize * get_explicit_type_size( outputType ) * 4; |
| BufferOwningPtr<char> resultValues(malloc( resultValuesSize )); |
| float lod_float = (float)lod; |
| if( gTestMipmaps ) |
| { |
| if(gDebugTrace) |
| log_info(" - Working at mip level %d\n", lod); |
| error = clSetKernelArg( kernel, idx, sizeof(float), &lod_float); |
| } |
| for( int q = 0; q < loopCount; q++ ) |
| { |
| float offset = float_offsets[ q % float_offset_count ]; |
| |
| // Init the coordinates |
| InitFloatCoords( imageInfo, imageSampler, xOffsetValues, yOffsetValues, zOffsetValues, |
| q>=float_offset_count ? -offset: offset, |
| q>=float_offset_count ? offset: -offset, |
| q>=float_offset_count ? -offset: offset, |
| imageSampler->normalized_coords, d, lod ); |
| |
| error = clEnqueueWriteBuffer( queue, xOffsets, CL_TRUE, 0, sizeof(cl_float) * imageInfo->height * imageInfo->width * imageInfo->arraySize, xOffsetValues, 0, NULL, NULL ); |
| test_error( error, "Unable to write x offsets" ); |
| error = clEnqueueWriteBuffer( queue, yOffsets, CL_TRUE, 0, sizeof(cl_float) * imageInfo->height * imageInfo->width * imageInfo->arraySize, yOffsetValues, 0, NULL, NULL ); |
| test_error( error, "Unable to write y offsets" ); |
| error = clEnqueueWriteBuffer( queue, zOffsets, CL_TRUE, 0, sizeof(cl_float) * imageInfo->height * imageInfo->width * imageInfo->arraySize, zOffsetValues, 0, NULL, NULL ); |
| test_error( error, "Unable to write z offsets" ); |
| |
| |
| memset( resultValues, 0xff, resultValuesSize ); |
| clEnqueueWriteBuffer( queue, results, CL_TRUE, 0, resultValuesSize, resultValues, 0, NULL, NULL ); |
| |
| // Figure out thread dimensions |
| threads[0] = (size_t)width_lod; |
| threads[1] = (size_t)height_lod; |
| threads[2] = (size_t)imageInfo->arraySize; |
| |
| // Run the kernel |
| error = clEnqueueNDRangeKernel( queue, kernel, 3, NULL, threads, NULL, 0, NULL, NULL ); |
| test_error( error, "Unable to run kernel" ); |
| |
| // Get results |
| error = clEnqueueReadBuffer( queue, results, CL_TRUE, 0, width_lod * height_lod * imageInfo->arraySize * get_explicit_type_size( outputType ) * 4, resultValues, 0, NULL, NULL ); |
| test_error( error, "Unable to read results from kernel" ); |
| if( gDebugTrace ) |
| log_info( " results read\n" ); |
| |
| // Validate results element by element |
| char *imagePtr = (char *)imageValues + nextLevelOffset; |
| |
| if((imageInfo->format->image_channel_order == CL_DEPTH) && (outputType == kFloat) ) |
| { |
| // Validate float results |
| float *resultPtr = (float *)(char *)resultValues; |
| float expected[4], error=0.0f; |
| float maxErr = get_max_relative_error( imageInfo->format, imageSampler, 1 /*3D*/, CL_FILTER_LINEAR == imageSampler->filter_mode ); |
| |
| for( size_t z = 0, j = 0; z < imageInfo->arraySize; z++ ) |
| { |
| for( size_t y = 0; y < height_lod; y++ ) |
| { |
| for( size_t x = 0; x < width_lod; x++, j++ ) |
| { |
| // Step 1: go through and see if the results verify for the pixel |
| // For the normalized case on a GPU we put in offsets to the X, Y and Z to see if we land on the |
| // right pixel. This addresses the significant inaccuracy in GPU normalization in OpenCL 1.0. |
| int checkOnlyOnePixel = 0; |
| int found_pixel = 0; |
| float offset = NORM_OFFSET; |
| if (!imageSampler->normalized_coords || imageSampler->filter_mode != CL_FILTER_NEAREST || NORM_OFFSET == 0 |
| #if defined( __APPLE__ ) |
| // Apple requires its CPU implementation to do correctly rounded address arithmetic in all modes |
| || gDeviceType != CL_DEVICE_TYPE_GPU |
| #endif |
| ) |
| offset = 0.0f; // Loop only once |
| |
| for (float norm_offset_x = -offset; norm_offset_x <= offset && !found_pixel ; norm_offset_x += NORM_OFFSET) { |
| for (float norm_offset_y = -offset; norm_offset_y <= offset && !found_pixel ; norm_offset_y += NORM_OFFSET) { |
| for (float norm_offset_z = -offset; norm_offset_z <= NORM_OFFSET && !found_pixel; norm_offset_z += NORM_OFFSET) { |
| |
| int hasDenormals = 0; |
| FloatPixel maxPixel = sample_image_pixel_float_offset( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected, 0, &hasDenormals, lod ); |
| |
| float err1 = |
| ABS_ERROR(resultPtr[0], expected[0]); |
| // Clamp to the minimum absolute error for the format |
| if (err1 > 0 && err1 < formatAbsoluteError) { err1 = 0.0f; } |
| float maxErr1 = MAX( maxErr * maxPixel.p[0], FLT_MIN ); |
| |
| if( ! (err1 <= maxErr1) ) |
| { |
| // Try flushing the denormals |
| if( hasDenormals ) |
| { |
| // If implementation decide to flush subnormals to zero, |
| // max error needs to be adjusted |
| maxErr1 += 4 * FLT_MIN; |
| |
| maxPixel = sample_image_pixel_float_offset( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected, 0, NULL, lod ); |
| |
| err1 = ABS_ERROR(resultPtr[0], |
| expected[0]); |
| } |
| } |
| |
| found_pixel = (err1 <= maxErr1); |
| }//norm_offset_z |
| }//norm_offset_y |
| }//norm_offset_x |
| |
| // Step 2: If we did not find a match, then print out debugging info. |
| if (!found_pixel) { |
| // For the normalized case on a GPU we put in offsets to the X and Y to see if we land on the |
| // right pixel. This addresses the significant inaccuracy in GPU normalization in OpenCL 1.0. |
| checkOnlyOnePixel = 0; |
| int shouldReturn = 0; |
| for (float norm_offset_x = -offset; norm_offset_x <= offset && !checkOnlyOnePixel; norm_offset_x += NORM_OFFSET) { |
| for (float norm_offset_y = -offset; norm_offset_y <= offset && !checkOnlyOnePixel; norm_offset_y += NORM_OFFSET) { |
| for (float norm_offset_z = -offset; norm_offset_z <= offset && !checkOnlyOnePixel; norm_offset_z += NORM_OFFSET) { |
| |
| int hasDenormals = 0; |
| FloatPixel maxPixel = sample_image_pixel_float_offset( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected, 0, &hasDenormals, lod ); |
| |
| float err1 = ABS_ERROR(resultPtr[0], |
| expected[0]); |
| float maxErr1 = MAX( maxErr * maxPixel.p[0], FLT_MIN ); |
| |
| |
| if( ! (err1 <= maxErr1) ) |
| { |
| // Try flushing the denormals |
| if( hasDenormals ) |
| { |
| maxErr1 += 4 * FLT_MIN; |
| |
| maxPixel = sample_image_pixel_float( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| imageSampler, expected, 0, NULL, lod ); |
| |
| err1 = ABS_ERROR(resultPtr[0], |
| expected[0]); |
| } |
| } |
| |
| if( ! (err1 <= maxErr1) ) |
| { |
| log_error("FAILED norm_offsets: %g , %g , %g:\n", norm_offset_x, norm_offset_y, norm_offset_z); |
| |
| float tempOut[4]; |
| shouldReturn |= determine_validation_error_offset_2D_array<float>( imagePtr, imageInfo, imageSampler, resultPtr, |
| expected, error, xOffsetValues[j], yOffsetValues[j], zOffsetValues[j], |
| norm_offset_x, norm_offset_y, norm_offset_z, j, |
| numTries, numClamped, true, lod ); |
| log_error( "Step by step:\n" ); |
| FloatPixel temp = sample_image_pixel_float_offset( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, tempOut, 1 /*verbose*/, &hasDenormals, lod); |
| log_error( "\tulps: %2.2f (max allowed: %2.2f)\n\n", |
| Ulp_Error( resultPtr[0], expected[0] ), |
| Ulp_Error( MAKE_HEX_FLOAT(0x1.000002p0f, 0x1000002L, -24) + maxErr, MAKE_HEX_FLOAT(0x1.000002p0f, 0x1000002L, -24) ) ); |
| } else { |
| log_error("Test error: we should have detected this passing above.\n"); |
| } |
| }//norm_offset_z |
| }//norm_offset_y |
| }//norm_offset_x |
| if( shouldReturn ) |
| return 1; |
| } // if (!found_pixel) |
| |
| resultPtr += 1; |
| } |
| } |
| } |
| } |
| /* |
| * FLOAT output type, order=CL_sRGBA, CL_sRGB, CL_sRGBx, CL_BGRA |
| */ |
| else if(is_sRGBA_order(imageInfo->format->image_channel_order) && (outputType == kFloat) ) |
| { |
| // Validate float results |
| float *resultPtr = (float *)(char *)resultValues; |
| float expected[4], error=0.0f; |
| float maxErr = get_max_relative_error( imageInfo->format, imageSampler, 1 /*3D*/, CL_FILTER_LINEAR == imageSampler->filter_mode ); |
| |
| for( size_t z = 0, j = 0; z < imageInfo->arraySize; z++ ) |
| { |
| for( size_t y = 0; y < height_lod; y++ ) |
| { |
| for( size_t x = 0; x < width_lod; x++, j++ ) |
| { |
| // Step 1: go through and see if the results verify for the pixel |
| // For the normalized case on a GPU we put in offsets to the X, Y and Z to see if we land on the |
| // right pixel. This addresses the significant inaccuracy in GPU normalization in OpenCL 1.0. |
| int checkOnlyOnePixel = 0; |
| int found_pixel = 0; |
| float offset = NORM_OFFSET; |
| if (!imageSampler->normalized_coords || imageSampler->filter_mode != CL_FILTER_NEAREST || NORM_OFFSET == 0 |
| #if defined( __APPLE__ ) |
| // Apple requires its CPU implementation to do correctly rounded address arithmetic in all modes |
| || gDeviceType != CL_DEVICE_TYPE_GPU |
| #endif |
| ) |
| offset = 0.0f; // Loop only once |
| |
| for (float norm_offset_x = -offset; norm_offset_x <= offset && !found_pixel ; norm_offset_x += NORM_OFFSET) { |
| for (float norm_offset_y = -offset; norm_offset_y <= offset && !found_pixel ; norm_offset_y += NORM_OFFSET) { |
| for (float norm_offset_z = -offset; norm_offset_z <= NORM_OFFSET && !found_pixel; norm_offset_z += NORM_OFFSET) { |
| |
| int hasDenormals = 0; |
| FloatPixel maxPixel = sample_image_pixel_float_offset( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected, 0, &hasDenormals, lod ); |
| |
| float err1 = |
| ABS_ERROR(sRGBmap(resultPtr[0]), |
| sRGBmap(expected[0])); |
| float err2 = |
| ABS_ERROR(sRGBmap(resultPtr[1]), |
| sRGBmap(expected[1])); |
| float err3 = |
| ABS_ERROR(sRGBmap(resultPtr[2]), |
| sRGBmap(expected[2])); |
| float err4 = |
| ABS_ERROR(resultPtr[3], expected[3]); |
| float maxErr = 0.5; |
| |
| if( ! (err1 <= maxErr) || ! (err2 <= maxErr) || ! (err3 <= maxErr) || ! (err4 <= maxErr) ) |
| { |
| // Try flushing the denormals |
| if( hasDenormals ) |
| { |
| // If implementation decide to flush subnormals to zero, |
| // max error needs to be adjusted |
| maxErr += 4 * FLT_MIN; |
| |
| maxPixel = sample_image_pixel_float_offset( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected, 0, NULL, lod ); |
| |
| err1 = |
| ABS_ERROR(sRGBmap(resultPtr[0]), |
| sRGBmap(expected[0])); |
| err2 = |
| ABS_ERROR(sRGBmap(resultPtr[1]), |
| sRGBmap(expected[1])); |
| err3 = |
| ABS_ERROR(sRGBmap(resultPtr[2]), |
| sRGBmap(expected[2])); |
| err4 = ABS_ERROR(resultPtr[3], |
| expected[3]); |
| } |
| } |
| |
| found_pixel = (err1 <= maxErr) && (err2 <= maxErr) && (err3 <= maxErr) && (err4 <= maxErr); |
| }//norm_offset_z |
| }//norm_offset_y |
| }//norm_offset_x |
| |
| // Step 2: If we did not find a match, then print out debugging info. |
| if (!found_pixel) { |
| // For the normalized case on a GPU we put in offsets to the X and Y to see if we land on the |
| // right pixel. This addresses the significant inaccuracy in GPU normalization in OpenCL 1.0. |
| checkOnlyOnePixel = 0; |
| int shouldReturn = 0; |
| for (float norm_offset_x = -offset; norm_offset_x <= offset && !checkOnlyOnePixel; norm_offset_x += NORM_OFFSET) { |
| for (float norm_offset_y = -offset; norm_offset_y <= offset && !checkOnlyOnePixel; norm_offset_y += NORM_OFFSET) { |
| for (float norm_offset_z = -offset; norm_offset_z <= offset && !checkOnlyOnePixel; norm_offset_z += NORM_OFFSET) { |
| |
| int hasDenormals = 0; |
| FloatPixel maxPixel = sample_image_pixel_float_offset( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected, 0, &hasDenormals, lod ); |
| |
| float err1 = |
| ABS_ERROR(sRGBmap(resultPtr[0]), |
| sRGBmap(expected[0])); |
| float err2 = |
| ABS_ERROR(sRGBmap(resultPtr[1]), |
| sRGBmap(expected[1])); |
| float err3 = |
| ABS_ERROR(sRGBmap(resultPtr[2]), |
| sRGBmap(expected[2])); |
| float err4 = ABS_ERROR(resultPtr[3], |
| expected[3]); |
| float maxErr = 0.6; |
| |
| if( ! (err1 <= maxErr) || ! (err2 <= maxErr) || ! (err3 <= maxErr) || ! (err4 <= maxErr) ) |
| { |
| // Try flushing the denormals |
| if( hasDenormals ) |
| { |
| // If implementation decide to flush subnormals to zero, |
| // max error needs to be adjusted |
| maxErr += 4 * FLT_MIN; |
| |
| maxPixel = sample_image_pixel_float( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| imageSampler, expected, 0, NULL, lod ); |
| |
| err1 = ABS_ERROR( |
| sRGBmap(resultPtr[0]), |
| sRGBmap(expected[0])); |
| err2 = ABS_ERROR( |
| sRGBmap(resultPtr[1]), |
| sRGBmap(expected[1])); |
| err3 = ABS_ERROR( |
| sRGBmap(resultPtr[2]), |
| sRGBmap(expected[2])); |
| err4 = ABS_ERROR(resultPtr[3], |
| expected[3]); |
| } |
| } |
| |
| if( ! (err1 <= maxErr) || ! (err2 <= maxErr) || ! (err3 <= maxErr) || ! (err4 <= maxErr) ) |
| { |
| log_error("FAILED norm_offsets: %g , %g , %g:\n", norm_offset_x, norm_offset_y, norm_offset_z); |
| |
| float tempOut[4]; |
| shouldReturn |= determine_validation_error_offset_2D_array<float>( imagePtr, imageInfo, imageSampler, resultPtr, |
| expected, error, xOffsetValues[j], yOffsetValues[j], zOffsetValues[j], |
| norm_offset_x, norm_offset_y, norm_offset_z, j, |
| numTries, numClamped, true, lod ); |
| log_error( "Step by step:\n" ); |
| FloatPixel temp = sample_image_pixel_float_offset( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, tempOut, 1 /*verbose*/, &hasDenormals, lod); |
| log_error( "\tulps: %2.2f, %2.2f, %2.2f, %2.2f (max allowed: %2.2f)\n\n", |
| Ulp_Error( resultPtr[0], expected[0] ), |
| Ulp_Error( resultPtr[1], expected[1] ), |
| Ulp_Error( resultPtr[2], expected[2] ), |
| Ulp_Error( resultPtr[3], expected[3] ), |
| Ulp_Error( MAKE_HEX_FLOAT(0x1.000002p0f, 0x1000002L, -24) + maxErr, MAKE_HEX_FLOAT(0x1.000002p0f, 0x1000002L, -24) ) ); |
| } else { |
| log_error("Test error: we should have detected this passing above.\n"); |
| } |
| }//norm_offset_z |
| }//norm_offset_y |
| }//norm_offset_x |
| if( shouldReturn ) |
| return 1; |
| } // if (!found_pixel) |
| |
| resultPtr += 4; |
| } |
| } |
| } |
| } |
| /* |
| * FLOAT output type |
| */ |
| else if( outputType == kFloat ) |
| { |
| // Validate float results |
| float *resultPtr = (float *)(char *)resultValues; |
| float expected[4], error=0.0f; |
| float maxErr = get_max_relative_error( imageInfo->format, imageSampler, 1 /*3D*/, CL_FILTER_LINEAR == imageSampler->filter_mode ); |
| |
| for( size_t z = 0, j = 0; z < imageInfo->arraySize; z++ ) |
| { |
| for( size_t y = 0; y < height_lod; y++ ) |
| { |
| for( size_t x = 0; x < width_lod; x++, j++ ) |
| { |
| // Step 1: go through and see if the results verify for the pixel |
| // For the normalized case on a GPU we put in offsets to the X, Y and Z to see if we land on the |
| // right pixel. This addresses the significant inaccuracy in GPU normalization in OpenCL 1.0. |
| int checkOnlyOnePixel = 0; |
| int found_pixel = 0; |
| float offset = NORM_OFFSET; |
| if (!imageSampler->normalized_coords || imageSampler->filter_mode != CL_FILTER_NEAREST || NORM_OFFSET == 0 |
| #if defined( __APPLE__ ) |
| // Apple requires its CPU implementation to do correctly rounded address arithmetic in all modes |
| || gDeviceType != CL_DEVICE_TYPE_GPU |
| #endif |
| ) |
| offset = 0.0f; // Loop only once |
| |
| for (float norm_offset_x = -offset; norm_offset_x <= offset && !found_pixel ; norm_offset_x += NORM_OFFSET) { |
| for (float norm_offset_y = -offset; norm_offset_y <= offset && !found_pixel ; norm_offset_y += NORM_OFFSET) { |
| for (float norm_offset_z = -offset; norm_offset_z <= NORM_OFFSET && !found_pixel; norm_offset_z += NORM_OFFSET) { |
| |
| int hasDenormals = 0; |
| FloatPixel maxPixel = sample_image_pixel_float_offset( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected, 0, &hasDenormals, lod ); |
| |
| float err1 = |
| ABS_ERROR(resultPtr[0], expected[0]); |
| float err2 = |
| ABS_ERROR(resultPtr[1], expected[1]); |
| float err3 = |
| ABS_ERROR(resultPtr[2], expected[2]); |
| float err4 = |
| ABS_ERROR(resultPtr[3], expected[3]); |
| // Clamp to the minimum absolute error for the format |
| if (err1 > 0 && err1 < formatAbsoluteError) { err1 = 0.0f; } |
| if (err2 > 0 && err2 < formatAbsoluteError) { err2 = 0.0f; } |
| if (err3 > 0 && err3 < formatAbsoluteError) { err3 = 0.0f; } |
| if (err4 > 0 && err4 < formatAbsoluteError) { err4 = 0.0f; } |
| float maxErr1 = MAX( maxErr * maxPixel.p[0], FLT_MIN ); |
| float maxErr2 = MAX( maxErr * maxPixel.p[1], FLT_MIN ); |
| float maxErr3 = MAX( maxErr * maxPixel.p[2], FLT_MIN ); |
| float maxErr4 = MAX( maxErr * maxPixel.p[3], FLT_MIN ); |
| |
| if( ! (err1 <= maxErr1) || ! (err2 <= maxErr2) || ! (err3 <= maxErr3) || ! (err4 <= maxErr4) ) |
| { |
| // Try flushing the denormals |
| if( hasDenormals ) |
| { |
| // If implementation decide to flush subnormals to zero, |
| // max error needs to be adjusted |
| maxErr1 += 4 * FLT_MIN; |
| maxErr2 += 4 * FLT_MIN; |
| maxErr3 += 4 * FLT_MIN; |
| maxErr4 += 4 * FLT_MIN; |
| |
| maxPixel = sample_image_pixel_float_offset( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected, 0, NULL, lod ); |
| |
| err1 = ABS_ERROR(resultPtr[0], |
| expected[0]); |
| err2 = ABS_ERROR(resultPtr[1], |
| expected[1]); |
| err3 = ABS_ERROR(resultPtr[2], |
| expected[2]); |
| err4 = ABS_ERROR(resultPtr[3], |
| expected[3]); |
| } |
| } |
| |
| found_pixel = (err1 <= maxErr1) && (err2 <= maxErr2) && (err3 <= maxErr3) && (err4 <= maxErr4); |
| }//norm_offset_z |
| }//norm_offset_y |
| }//norm_offset_x |
| |
| // Step 2: If we did not find a match, then print out debugging info. |
| if (!found_pixel) { |
| // For the normalized case on a GPU we put in offsets to the X and Y to see if we land on the |
| // right pixel. This addresses the significant inaccuracy in GPU normalization in OpenCL 1.0. |
| checkOnlyOnePixel = 0; |
| int shouldReturn = 0; |
| for (float norm_offset_x = -offset; norm_offset_x <= offset && !checkOnlyOnePixel; norm_offset_x += NORM_OFFSET) { |
| for (float norm_offset_y = -offset; norm_offset_y <= offset && !checkOnlyOnePixel; norm_offset_y += NORM_OFFSET) { |
| for (float norm_offset_z = -offset; norm_offset_z <= offset && !checkOnlyOnePixel; norm_offset_z += NORM_OFFSET) { |
| |
| int hasDenormals = 0; |
| FloatPixel maxPixel = sample_image_pixel_float_offset( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected, 0, &hasDenormals, lod ); |
| |
| float err1 = ABS_ERROR(resultPtr[0], |
| expected[0]); |
| float err2 = ABS_ERROR(resultPtr[1], |
| expected[1]); |
| float err3 = ABS_ERROR(resultPtr[2], |
| expected[2]); |
| float err4 = ABS_ERROR(resultPtr[3], |
| expected[3]); |
| float maxErr1 = MAX( maxErr * maxPixel.p[0], FLT_MIN ); |
| float maxErr2 = MAX( maxErr * maxPixel.p[1], FLT_MIN ); |
| float maxErr3 = MAX( maxErr * maxPixel.p[2], FLT_MIN ); |
| float maxErr4 = MAX( maxErr * maxPixel.p[3], FLT_MIN ); |
| |
| |
| if( ! (err1 <= maxErr1) || ! (err2 <= maxErr2) || ! (err3 <= maxErr3) || ! (err4 <= maxErr4) ) |
| { |
| // Try flushing the denormals |
| if( hasDenormals ) |
| { |
| maxErr1 += 4 * FLT_MIN; |
| maxErr2 += 4 * FLT_MIN; |
| maxErr3 += 4 * FLT_MIN; |
| maxErr4 += 4 * FLT_MIN; |
| |
| maxPixel = sample_image_pixel_float( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| imageSampler, expected, 0, NULL, lod ); |
| |
| err1 = ABS_ERROR(resultPtr[0], |
| expected[0]); |
| err2 = ABS_ERROR(resultPtr[1], |
| expected[1]); |
| err3 = ABS_ERROR(resultPtr[2], |
| expected[2]); |
| err4 = ABS_ERROR(resultPtr[3], |
| expected[3]); |
| } |
| } |
| |
| if( ! (err1 <= maxErr1) || ! (err2 <= maxErr2) || ! (err3 <= maxErr3) || ! (err4 <= maxErr4) ) |
| { |
| log_error("FAILED norm_offsets: %g , %g , %g:\n", norm_offset_x, norm_offset_y, norm_offset_z); |
| |
| float tempOut[4]; |
| shouldReturn |= determine_validation_error_offset_2D_array<float>( imagePtr, imageInfo, imageSampler, resultPtr, |
| expected, error, xOffsetValues[j], yOffsetValues[j], zOffsetValues[j], |
| norm_offset_x, norm_offset_y, norm_offset_z, j, |
| numTries, numClamped, true, lod ); |
| log_error( "Step by step:\n" ); |
| FloatPixel temp = sample_image_pixel_float_offset( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, tempOut, 1 /*verbose*/, &hasDenormals, lod); |
| log_error( "\tulps: %2.2f, %2.2f, %2.2f, %2.2f (max allowed: %2.2f)\n\n", |
| Ulp_Error( resultPtr[0], expected[0] ), |
| Ulp_Error( resultPtr[1], expected[1] ), |
| Ulp_Error( resultPtr[2], expected[2] ), |
| Ulp_Error( resultPtr[3], expected[3] ), |
| Ulp_Error( MAKE_HEX_FLOAT(0x1.000002p0f, 0x1000002L, -24) + maxErr, MAKE_HEX_FLOAT(0x1.000002p0f, 0x1000002L, -24) ) ); |
| } else { |
| log_error("Test error: we should have detected this passing above.\n"); |
| } |
| }//norm_offset_z |
| }//norm_offset_y |
| }//norm_offset_x |
| if( shouldReturn ) |
| return 1; |
| } // if (!found_pixel) |
| |
| resultPtr += 4; |
| } |
| } |
| } |
| } |
| /* |
| * UINT output type |
| */ |
| else if( outputType == kUInt ) |
| { |
| // Validate unsigned integer results |
| unsigned int *resultPtr = (unsigned int *)(char *)resultValues; |
| unsigned int expected[4]; |
| float error; |
| for( size_t z = 0, j = 0; z < imageInfo->arraySize; z++ ) |
| { |
| for( size_t y = 0; y < height_lod; y++ ) |
| { |
| for( size_t x = 0; x < width_lod; x++, j++ ) |
| { |
| // Step 1: go through and see if the results verify for the pixel |
| // For the normalized case on a GPU we put in offsets to the X, Y and Z to see if we land on the |
| // right pixel. This addresses the significant inaccuracy in GPU normalization in OpenCL 1.0. |
| int checkOnlyOnePixel = 0; |
| int found_pixel = 0; |
| for (float norm_offset_x = -NORM_OFFSET; norm_offset_x <= NORM_OFFSET && !found_pixel && !checkOnlyOnePixel; norm_offset_x += NORM_OFFSET) { |
| for (float norm_offset_y = -NORM_OFFSET; norm_offset_y <= NORM_OFFSET && !found_pixel && !checkOnlyOnePixel; norm_offset_y += NORM_OFFSET) { |
| for (float norm_offset_z = -NORM_OFFSET; norm_offset_z <= NORM_OFFSET && !found_pixel && !checkOnlyOnePixel; norm_offset_z += NORM_OFFSET) { |
| |
| // If we are not on a GPU, or we are not normalized, then only test with offsets (0.0, 0.0) |
| // E.g., test one pixel. |
| if (!imageSampler->normalized_coords || gDeviceType != CL_DEVICE_TYPE_GPU || NORM_OFFSET == 0) { |
| norm_offset_x = 0.0f; |
| norm_offset_y = 0.0f; |
| norm_offset_z = 0.0f; |
| checkOnlyOnePixel = 1; |
| } |
| |
| if(gTestMipmaps) |
| sample_image_pixel_offset<unsigned int>( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected, lod ); |
| else |
| sample_image_pixel_offset<unsigned int>( imageValues, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected ); |
| |
| error = errMax( errMax( abs_diff_uint(expected[ 0 ], resultPtr[ 0 ]), abs_diff_uint(expected[ 1 ], resultPtr[ 1 ]) ), |
| errMax( abs_diff_uint(expected[ 2 ], resultPtr[ 2 ]), abs_diff_uint(expected[ 3 ], resultPtr[ 3 ]) ) ); |
| |
| if (error < MAX_ERR) |
| found_pixel = 1; |
| }//norm_offset_z |
| }//norm_offset_y |
| }//norm_offset_x |
| |
| // Step 2: If we did not find a match, then print out debugging info. |
| if (!found_pixel) { |
| // For the normalized case on a GPU we put in offsets to the X and Y to see if we land on the |
| // right pixel. This addresses the significant inaccuracy in GPU normalization in OpenCL 1.0. |
| checkOnlyOnePixel = 0; |
| int shouldReturn = 0; |
| for (float norm_offset_x = -NORM_OFFSET; norm_offset_x <= NORM_OFFSET && !checkOnlyOnePixel; norm_offset_x += NORM_OFFSET) { |
| for (float norm_offset_y = -NORM_OFFSET; norm_offset_y <= NORM_OFFSET && !checkOnlyOnePixel; norm_offset_y += NORM_OFFSET) { |
| for (float norm_offset_z = -NORM_OFFSET; norm_offset_z <= NORM_OFFSET && !checkOnlyOnePixel; norm_offset_z += NORM_OFFSET) { |
| |
| // If we are not on a GPU, or we are not normalized, then only test with offsets (0.0, 0.0) |
| // E.g., test one pixel. |
| if (!imageSampler->normalized_coords || gDeviceType != CL_DEVICE_TYPE_GPU || NORM_OFFSET == 0) { |
| norm_offset_x = 0.0f; |
| norm_offset_y = 0.0f; |
| norm_offset_z = 0.0f; |
| checkOnlyOnePixel = 1; |
| } |
| |
| if(gTestMipmaps) |
| sample_image_pixel_offset<unsigned int>( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected, lod ); |
| else |
| sample_image_pixel_offset<unsigned int>( imageValues, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected ); |
| |
| error = errMax( errMax( abs_diff_uint(expected[ 0 ], resultPtr[ 0 ]), abs_diff_uint(expected[ 1 ], resultPtr[ 1 ]) ), |
| errMax( abs_diff_uint(expected[ 2 ], resultPtr[ 2 ]), abs_diff_uint(expected[ 3 ], resultPtr[ 3 ]) ) ); |
| |
| if( error > MAX_ERR ) |
| { |
| log_error("FAILED norm_offsets: %g , %g , %g:\n", norm_offset_x, norm_offset_y, norm_offset_z); |
| shouldReturn |= determine_validation_error_offset_2D_array<unsigned int>( imagePtr, imageInfo, imageSampler, resultPtr, |
| expected, error, xOffsetValues[j], yOffsetValues[j], zOffsetValues[j], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| j, numTries, numClamped, false, lod ); |
| } else { |
| log_error("Test error: we should have detected this passing above.\n"); |
| } |
| }//norm_offset_z |
| }//norm_offset_y |
| }//norm_offset_x |
| if( shouldReturn ) |
| return 1; |
| } // if (!found_pixel) |
| |
| resultPtr += 4; |
| } |
| } |
| } |
| } |
| else |
| /* |
| * INT output type |
| */ |
| { |
| // Validate integer results |
| int *resultPtr = (int *)(char *)resultValues; |
| int expected[4]; |
| float error; |
| for( size_t z = 0, j = 0; z < imageInfo->arraySize; z++ ) |
| { |
| for( size_t y = 0; y < height_lod; y++ ) |
| { |
| for( size_t x = 0; x < width_lod; x++, j++ ) |
| { |
| // Step 1: go through and see if the results verify for the pixel |
| // For the normalized case on a GPU we put in offsets to the X, Y and Z to see if we land on the |
| // right pixel. This addresses the significant inaccuracy in GPU normalization in OpenCL 1.0. |
| int checkOnlyOnePixel = 0; |
| int found_pixel = 0; |
| for (float norm_offset_x = -NORM_OFFSET; norm_offset_x <= NORM_OFFSET && !found_pixel && !checkOnlyOnePixel; norm_offset_x += NORM_OFFSET) { |
| for (float norm_offset_y = -NORM_OFFSET; norm_offset_y <= NORM_OFFSET && !found_pixel && !checkOnlyOnePixel; norm_offset_y += NORM_OFFSET) { |
| for (float norm_offset_z = -NORM_OFFSET; norm_offset_z <= NORM_OFFSET && !found_pixel && !checkOnlyOnePixel; norm_offset_z += NORM_OFFSET) { |
| |
| // If we are not on a GPU, or we are not normalized, then only test with offsets (0.0, 0.0) |
| // E.g., test one pixel. |
| if (!imageSampler->normalized_coords || gDeviceType != CL_DEVICE_TYPE_GPU || NORM_OFFSET == 0) { |
| norm_offset_x = 0.0f; |
| norm_offset_y = 0.0f; |
| norm_offset_z = 0.0f; |
| checkOnlyOnePixel = 1; |
| } |
| |
| if(gTestMipmaps) |
| sample_image_pixel_offset<int>( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected, lod ); |
| else |
| sample_image_pixel_offset<int>( imageValues, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected ); |
| |
| error = errMax( errMax( abs_diff_int(expected[ 0 ], resultPtr[ 0 ]), abs_diff_int(expected[ 1 ], resultPtr[ 1 ]) ), |
| errMax( abs_diff_int(expected[ 2 ], resultPtr[ 2 ]), abs_diff_int(expected[ 3 ], resultPtr[ 3 ]) ) ); |
| |
| if (error < MAX_ERR) |
| found_pixel = 1; |
| }//norm_offset_z |
| }//norm_offset_y |
| }//norm_offset_x |
| |
| // Step 2: If we did not find a match, then print out debugging info. |
| if (!found_pixel) { |
| // For the normalized case on a GPU we put in offsets to the X and Y to see if we land on the |
| // right pixel. This addresses the significant inaccuracy in GPU normalization in OpenCL 1.0. |
| checkOnlyOnePixel = 0; |
| int shouldReturn = 0; |
| for (float norm_offset_x = -NORM_OFFSET; norm_offset_x <= NORM_OFFSET && !checkOnlyOnePixel; norm_offset_x += NORM_OFFSET) { |
| for (float norm_offset_y = -NORM_OFFSET; norm_offset_y <= NORM_OFFSET && !checkOnlyOnePixel; norm_offset_y += NORM_OFFSET) { |
| for (float norm_offset_z = -NORM_OFFSET; norm_offset_z <= NORM_OFFSET && !checkOnlyOnePixel; norm_offset_z += NORM_OFFSET) { |
| |
| // If we are not on a GPU, or we are not normalized, then only test with offsets (0.0, 0.0) |
| // E.g., test one pixel. |
| if (!imageSampler->normalized_coords || gDeviceType != CL_DEVICE_TYPE_GPU || NORM_OFFSET == 0 || NORM_OFFSET == 0 || NORM_OFFSET == 0) { |
| norm_offset_x = 0.0f; |
| norm_offset_y = 0.0f; |
| norm_offset_z = 0.0f; |
| checkOnlyOnePixel = 1; |
| } |
| |
| if(gTestMipmaps) |
| sample_image_pixel_offset<int>( imagePtr, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected, lod ); |
| else |
| sample_image_pixel_offset<int>( imageValues, imageInfo, |
| xOffsetValues[ j ], yOffsetValues[ j ], zOffsetValues[ j ], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| imageSampler, expected, 0 ); |
| |
| error = errMax( errMax( abs_diff_int(expected[ 0 ], resultPtr[ 0 ]), abs_diff_int(expected[ 1 ], resultPtr[ 1 ]) ), |
| errMax( abs_diff_int(expected[ 2 ], resultPtr[ 2 ]), abs_diff_int(expected[ 3 ], resultPtr[ 3 ]) ) ); |
| |
| if( error > MAX_ERR ) |
| { |
| log_error("FAILED norm_offsets: %g , %g , %g:\n", norm_offset_x, norm_offset_y, norm_offset_z); |
| shouldReturn |= determine_validation_error_offset_2D_array<int>( imagePtr, imageInfo, imageSampler, resultPtr, |
| expected, error, xOffsetValues[j], yOffsetValues[j], zOffsetValues[j], |
| norm_offset_x, norm_offset_y, norm_offset_z, |
| j, numTries, numClamped, false, lod ); |
| } else { |
| log_error("Test error: we should have detected this passing above.\n"); |
| } |
| }//norm_offset_z |
| }//norm_offset_y |
| }//norm_offset_x |
| if( shouldReturn ) |
| return 1; |
| } // if (!found_pixel) |
| |
| resultPtr += 4; |
| } |
| } |
| } |
| } |
| } |
| { |
| nextLevelOffset += width_lod * height_lod * imageInfo->arraySize * get_pixel_size(imageInfo->format); |
| width_lod = ( width_lod >> 1 ) ? ( width_lod >> 1 ) : 1; |
| height_lod = ( height_lod >> 1 ) ? ( height_lod >> 1 ) : 1; |
| } |
| } |
| |
| return numTries != MAX_TRIES || numClamped != MAX_CLAMPED; |
| } |
| |
| int test_read_image_set_2D_array( cl_device_id device, cl_context context, cl_command_queue queue, cl_image_format *format, image_sampler_data *imageSampler, |
| bool floatCoords, ExplicitType outputType ) |
| { |
| char programSrc[10240]; |
| const char *ptr; |
| const char *readFormat; |
| RandomSeed seed( gRandomSeed ); |
| |
| const char *KernelSourcePattern = NULL; |
| |
| int error; |
| |
| clProgramWrapper program; |
| clKernelWrapper kernel; |
| |
| // Get operating parameters |
| size_t maxWidth, maxHeight, maxArraySize; |
| cl_ulong maxAllocSize, memSize; |
| image_descriptor imageInfo = { 0x0 }; |
| size_t pixelSize; |
| |
| imageInfo.format = format; |
| imageInfo.type = CL_MEM_OBJECT_IMAGE2D_ARRAY; |
| pixelSize = get_pixel_size( imageInfo.format ); |
| |
| error = clGetDeviceInfo( device, CL_DEVICE_IMAGE2D_MAX_WIDTH, sizeof( maxWidth ), &maxWidth, NULL ); |
| error |= clGetDeviceInfo( device, CL_DEVICE_IMAGE2D_MAX_HEIGHT, sizeof( maxHeight ), &maxHeight, NULL ); |
| error |= clGetDeviceInfo( device, CL_DEVICE_IMAGE_MAX_ARRAY_SIZE, sizeof( maxArraySize ), &maxArraySize, NULL ); |
| error |= clGetDeviceInfo( device, CL_DEVICE_MAX_MEM_ALLOC_SIZE, sizeof( maxAllocSize ), &maxAllocSize, NULL ); |
| error |= clGetDeviceInfo( device, CL_DEVICE_GLOBAL_MEM_SIZE, sizeof( memSize ), &memSize, NULL ); |
| test_error( error, "Unable to get max image 3D size from device" ); |
| |
| if (memSize > (cl_ulong)SIZE_MAX) { |
| memSize = (cl_ulong)SIZE_MAX; |
| } |
| |
| // Determine types |
| if( outputType == kInt ) |
| readFormat = "i"; |
| else if( outputType == kUInt ) |
| readFormat = "ui"; |
| else // kFloat |
| readFormat = "f"; |
| |
| // Construct the source |
| const char *samplerArg = samplerKernelArg; |
| char samplerVar[ 1024 ] = ""; |
| if( gUseKernelSamplers ) |
| { |
| get_sampler_kernel_code( imageSampler, samplerVar ); |
| samplerArg = ""; |
| } |
| |
| const char *imageType; |
| const char *imageElement; |
| if (format->image_channel_order == CL_DEPTH) |
| { |
| imageType = "image2d_array_depth_t"; |
| imageElement = ""; |
| } |
| else |
| { |
| imageType = "image2d_array_t"; |
| imageElement = "4"; |
| } |
| |
| // Construct the source |
| if(gtestTypesToRun & kReadTests) |
| { |
| KernelSourcePattern = read2DArrayKernelSourcePattern; |
| } |
| else |
| { |
| KernelSourcePattern = read_write2DArrayKernelSourcePattern; |
| } |
| |
| // Construct the source |
| sprintf( programSrc, |
| KernelSourcePattern, |
| imageType, |
| samplerArg, get_explicit_type_name( outputType ), |
| imageElement, |
| gTestMipmaps ? ", float lod" : " ", |
| samplerVar, |
| gTestMipmaps ? offset2DarraySourceLod : offset2DarraySource, |
| floatCoords ? float2DArrayUnnormalizedCoordKernelSource : int2DArrayCoordKernelSource, |
| readFormat, |
| gTestMipmaps ? ", lod" : " " ); |
| |
| ptr = programSrc; |
| error = create_single_kernel_helper(context, &program, &kernel, 1, &ptr, |
| "sample_kernel"); |
| test_error( error, "Unable to create testing kernel" ); |
| |
| // Run tests |
| |
| if( gTestSmallImages ) |
| { |
| for( imageInfo.width = 1; imageInfo.width < 13; imageInfo.width++ ) |
| { |
| imageInfo.rowPitch = imageInfo.width * pixelSize; |
| |
| for( imageInfo.height = 1; imageInfo.height < 9; imageInfo.height++ ) |
| { |
| imageInfo.slicePitch = imageInfo.rowPitch * imageInfo.height; |
| for( imageInfo.arraySize = 2; imageInfo.arraySize < 9; imageInfo.arraySize++ ) |
| { |
| if( gTestMipmaps ) |
| imageInfo.num_mip_levels = (size_t) random_in_range(2, compute_max_mip_levels(imageInfo.width, imageInfo.height, 0)-1, seed); |
| |
| if( gDebugTrace ) |
| log_info( " at size %d,%d,%d\n", (int)imageInfo.width, (int)imageInfo.height, (int)imageInfo.arraySize ); |
| int retCode = test_read_image_2D_array( context, queue, kernel, &imageInfo, imageSampler, floatCoords, outputType, seed ); |
| if( retCode ) |
| return retCode; |
| } |
| } |
| } |
| } |
| else if( gTestMaxImages ) |
| { |
| // Try a specific set of maximum sizes |
| size_t numbeOfSizes; |
| size_t sizes[100][3]; |
| |
| get_max_sizes(&numbeOfSizes, 100, sizes, maxWidth, maxHeight, 1, maxArraySize, maxAllocSize, memSize, CL_MEM_OBJECT_IMAGE2D_ARRAY, imageInfo.format, CL_TRUE); |
| |
| for( size_t idx = 0; idx < numbeOfSizes; idx++ ) |
| { |
| imageInfo.width = sizes[ idx ][ 0 ]; |
| imageInfo.height = sizes[ idx ][ 1 ]; |
| imageInfo.arraySize = sizes[ idx ][ 2 ]; |
| imageInfo.rowPitch = imageInfo.width * pixelSize; |
| imageInfo.slicePitch = imageInfo.height * imageInfo.rowPitch; |
| if( gTestMipmaps ) |
| imageInfo.num_mip_levels = (size_t) random_in_range(2, compute_max_mip_levels(imageInfo.width, imageInfo.height, 0)-1, seed); |
| cl_ulong size = (cl_ulong)imageInfo.slicePitch * (cl_ulong)imageInfo.arraySize * 4 * 4; |
| // Loop until we get a size that a) will fit in the max alloc size and b) that an allocation of that |
| // image, the result array, plus offset arrays, will fit in the global ram space |
| while( size > maxAllocSize || ( size * 3 ) > memSize ) |
| { |
| if(imageInfo.arraySize == 1) |
| { |
| // ArraySize cannot be 0. |
| break; |
| } |
| imageInfo.arraySize--; |
| size = (cl_ulong)imageInfo.slicePitch * (cl_ulong)imageInfo.arraySize * 4 * 4; |
| } |
| |
| while( size > maxAllocSize || ( size * 3 ) > memSize ) |
| { |
| imageInfo.height--; |
| imageInfo.slicePitch = imageInfo.height * imageInfo.rowPitch; |
| size = (cl_ulong)imageInfo.slicePitch * (cl_ulong)imageInfo.arraySize * 4 * 4; |
| } |
| log_info("Testing %d x %d x %d\n", (int)sizes[ idx ][ 0 ], (int)sizes[ idx ][ 1 ], (int)sizes[ idx ][ 2 ]); |
| if( gDebugTrace ) |
| log_info( " at max size %d,%d,%d\n", (int)sizes[ idx ][ 0 ], (int)sizes[ idx ][ 1 ], (int)sizes[ idx ][ 2 ] ); |
| int retCode = test_read_image_2D_array( context, queue, kernel, &imageInfo, imageSampler, floatCoords, outputType, seed ); |
| if( retCode ) |
| return retCode; |
| } |
| } |
| else if( gTestRounding ) |
| { |
| size_t typeRange = 1 << ( get_format_type_size( imageInfo.format ) * 8 ); |
| imageInfo.height = typeRange / 256; |
| imageInfo.width = (size_t)( typeRange / (cl_ulong)imageInfo.height ); |
| imageInfo.arraySize = 2; |
| |
| imageInfo.rowPitch = imageInfo.width * pixelSize; |
| imageInfo.slicePitch = imageInfo.height * imageInfo.rowPitch; |
| int retCode = test_read_image_2D_array( context, queue, kernel, &imageInfo, imageSampler, floatCoords, outputType, seed ); |
| if( retCode ) |
| return retCode; |
| } |
| else |
| { |
| int maxWidthRange = (int) reduceImageSizeRange(maxWidth); |
| int maxHeighthRange = (int) reduceImageSizeRange(maxHeight); |
| int maxArraySizeRange = (int) reduceImageDepth(maxArraySize); |
| |
| for( int i = 0; i < NUM_IMAGE_ITERATIONS; i++ ) |
| { |
| cl_ulong size; |
| // Loop until we get a size that a) will fit in the max alloc size and b) that an allocation of that |
| // image, the result array, plus offset arrays, will fit in the global ram space |
| do |
| { |
| imageInfo.width = (size_t)random_log_in_range( 16, maxWidthRange, seed ); |
| imageInfo.height = (size_t)random_log_in_range( 16, maxHeighthRange, seed ); |
| imageInfo.arraySize = (size_t)random_log_in_range( 8, maxArraySizeRange, seed ); |
| |
| imageInfo.rowPitch = imageInfo.width * pixelSize; |
| imageInfo.slicePitch = imageInfo.rowPitch * imageInfo.height; |
| |
| if( gTestMipmaps ) |
| { |
| imageInfo.num_mip_levels = random_in_range(2,compute_max_mip_levels(imageInfo.width, imageInfo.height, 0) - 1, seed); |
| //Need to take into account the output buffer size, otherwise we will end up with input buffer that is exceeding MaxAlloc |
| size = (cl_ulong) 4*compute_mipmapped_image_size( imageInfo ) * get_explicit_type_size( outputType ); |
| } |
| else |
| { |
| if( gEnablePitch ) |
| { |
| size_t extraWidth = (int)random_log_in_range( 0, 64, seed ); |
| imageInfo.rowPitch += extraWidth * pixelSize; |
| |
| size_t extraHeight = (int)random_log_in_range( 0, 64, seed ); |
| imageInfo.slicePitch = imageInfo.rowPitch * (imageInfo.height + extraHeight); |
| } |
| |
| size = (cl_ulong)imageInfo.slicePitch * (cl_ulong)imageInfo.arraySize * 4 * 4; |
| } |
| } while( size > maxAllocSize || ( size * 3 ) > memSize ); |
| |
| if( gDebugTrace ) |
| { |
| log_info( " at size %d,%d,%d (pitch %d,%d) out of %d,%d,%d\n", (int)imageInfo.width, (int)imageInfo.height, (int)imageInfo.arraySize, (int)imageInfo.rowPitch, (int)imageInfo.slicePitch, (int)maxWidth, (int)maxHeight, (int)maxArraySize ); |
| if ( gTestMipmaps ) |
| log_info(" and %d mip levels\n", (int) imageInfo.num_mip_levels); |
| } |
| int retCode = test_read_image_2D_array( context, queue, kernel, &imageInfo, imageSampler, floatCoords, outputType, seed ); |
| if( retCode ) |
| return retCode; |
| } |
| } |
| |
| return 0; |
| } |
