* enable compilation of INSTANCES_ONLY for Windows
* suppress ROCMChecks warnings on GoogleTests
* suppress -Wfloat-equal warning on GoogleTests
---------
Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
* adding files for F32 example
* adding functioning implementation with scalar multiplication and unary operator support
* added fp 16 type check in unary square
* updating scalar multiplication as an operator
* functioning version with scalar operator
* changing strides for col major
* updated column major implementation
* working column major implementation
* cleaned up comments, rearranged/renamed files
* Support multi AB for grouped conv fwd xdl
* Add instances
* Add client example
* Add example
* Add interface test
* Minor fixes
Minor fixes
Minor fixes
* Comment fixes
* Fixes
* Reference fix
* Test xdl fixes
* Improve multi_ab interface test
* Add support for mixed precision in contraction scale and bilinear (#936)
* Extract common functionality to separate files
* Reference contraction: Remove incorrect consts from type_converts
* Reference contraction: Add missing type_convert for dst value
* Reference contraction: Fix incorrect order of B matrix dimensions
* Add support for mixed precision in contraction scale and bilinear
* Move using statements from instances to a common file
* Move using statements from examples to a common file
* Fix the order of B matrix dimensions across examples and profiler
* Fix the computation of error threshold
* Make ComputeDataType an optional argument
* Include possible DataType -> ComputeDataType casting error in the threshold
* Remove commented code
* Make the ComputeDataType an optional argument in instance
---------
Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
* workaround nan problem by changing output to fp16
* enable f8/bf8 gemm tests on MI200
* workaround f16 to f8 conversion
---------
Co-authored-by: Jing Zhang <jizha@amd.com>
* Extract common functionality to separate files
* Reference contraction: Remove incorrect consts from type_converts
* Reference contraction: Add missing type_convert for dst value
* Reference contraction: Fix incorrect order of B matrix dimensions
* Add support for mixed precision in contraction scale and bilinear
* Move using statements from instances to a common file
* Move using statements from examples to a common file
* Fix the order of B matrix dimensions across examples and profiler
* Fix the computation of error threshold
* Make ComputeDataType an optional argument
* Include possible DataType -> ComputeDataType casting error in the threshold
* Remove commented code
* Add basic fp8 definitions and prn-generator
* Format
* Add fp8<->fp32 type_convert
* Format
* Split type_convert and cast_to/from_f8
* Format
* Minor fix
* Minor fix
* Move fp8 utils to a separate header
* Add elementwise ops
* Add fp8_convert_sr
* Format
* Add element op
* Eliminate magic numbers
* Split f8_convert_sr in host and device
* Format
* Add some constexpr
* Add a datatype test
* Format
* Another format
* Add fp8<->fp16 tests
* Update type_converts
* Format
* Add fp16 casting functions
* Format
* Use seed as a runtime arg
* Use element location for PRNG
* Format
* Add fp8<->fp16 to PassThrough element op
* Clean up
* Merge host and device implementations
* Add comments on rounding modes
* Remove leftover code
* Put type_converts into a separate header
* Put random number gen to a separate header
* Rearrange f8_utils' namespaces
* Refactor type_convert.hpp
* Move f8_t definition
* Add TypeConvert class and start refactoring
* Refactor TypeConvert as a struct
* Get back to template functions type_convert
* Add a type_convert_bf16_rtn, set rtz as default
* Clean up
* Add UnaryConvertPrecision struct for high-precision workloads
* Format
* Update type_convert to UnaryConvert on threadwise level
* Update UnaryConvertPrecision
* Format
* Fix chmod
* Add a flag to pick converion method
* Format
* Remove the added flag
* Merge elementwise op with type conversion
* Move type_convert to elemwise op, update the op
* Update type_convert_precision -> bf16_convert_rtn
* Clean up
* Update comments
* Update the CK_WORKAROUND_DENORM_FIX flag handling
* Update the unneeded op to work but warn user
* Remove the message
* Use a PassThrough instead of ConvertBF16RTN to calcaulate reference
* Format
* Add missing include
* Rename to proper naming
* Add example of groupnorm + swish
* Extract duplicate code in example
* Add groupnorm + swish instances
* Ractor instance generation, split into multiple cpp file
* Add external api and client example
* Refine profiler message
* Use ck math version of exp
* Refine problem size in example
* Add host version of exp
* Add conv perlayer quantization
* Add gemm_dlops quantization
* Support int8 for innerproduct
* Refine gemm dlops int8 kernel parameter
* Support gfx908(MI100) and gfx90a(MI200)
* clang-format
* Rename example number
* Support different layout for d tensor
* Add conv dlops perchannel quantization example
* Move to example 40
* Extract the common code for different platform (dlops and xdlops)
* Move ot subfolder. Prepare to add other op of quantization
* Refine the quantization instance library
* Add conv dl instances and client example
* Remove unnecessary type
* Add gemm quantization instance
* Add external api and client example
* Refine num_bytes
* Separete different layout to different cpp
* Add more xdl instances
* Revert "Remove unnecessary type"
This reverts commit 820869182f.
* Remove CShuffleDataType in dlops
Let acc and CShuffleDataType be the same in xdlops
---------
Co-authored-by: zjing14 <zhangjing14@gmail.com>
* add instance for gemm bias softmax gemm
* add client example
* change CGridDesc_G_M_N to CGridDesc_G_M_O
* add gridwise
* change c grid name
* device add d0s data
* fix 08 client_example
* add example 47_fused_attention
* example output correct
* add d0 to example
* add d0 element op
* rechange instance code
* change Acc0ElementwiseOperation to C0DEElementwiseOperation
* change example name
* update instance for cdeelementwiseop
* add bhalf_t ScaleAdd
* add test
* not surport geem1 bias
* remove some ignore
* fix test bug
* File renaming and class renaming for device element-wise operation
* Add batchnorm-infer instances, external API and client example
* Add batchnorm-infer profiler module and gtests
* Remove file device_elementwise_extension.hpp and move NormalizeInInfer operation to element_wise_operation.hpp
* Remove the using of class aliasing for DeviceElementwiseForBatchNormInfer
* Rename class and file due to conflict from device_elementwise_2d.hpp
* Fix namespace in batcnnorm_infer_nhwc client example
* start add example
* add multiple d fp16 example
* device transfer elementwiseop to gridwise
* gridwise add multiple d
* change example for multiple d
* fix spill registers
* fix for passthrough element op
* fix int8 overflow
* change example file name
* add instance for dl multiple d
* example add DsDataType
* remove grouped_convolution_forward_dl.hpp
* add head file(was deleted before)
* fix not support device issue
* format
* remove passthrough check
Co-authored-by: letaoqin <letaoqin@amd.com>
* FastGelu support for more data types.
* AddFastGelu & FastGelu instances.
* Client example.
* clang-format
* Remove unused stride variable.
* Add new line at EOF.
Co-authored-by: Adam Osewski <aosewski@amd.com>
* Add conv2d requant example
* Fix bash error
* Rename example
* 1. Rename gemm quantization
2. shares the requantization lambda function with conv
* Refine declare type
* Add conv bias relu quantization exmaple
* clang format
* Fix compile error due to merge develop
* Fix CI error
* Extract quantization post operation into another file
* Support quantization for non piecewise linear function
* Add instance for conv quantization
* Add convolution quantization factory
* Add convolution quantization client example
* Add more instances with different template parameters
* clang format
* Sync the naming with the develop
* Add groupnorm example by layernorm
1. Reference is not ready
2. shape of gamma and beta need to be fix
* Let shape of gamma and beta can be same as x
* Modify test, instance and client example
* [What] Fix bug of layernorm for greater than 2 dimension.
[Why] We need to get upper length from merge transform instead of embed transform.
* Add reference for groupnorm
* Fuse sigmoid after groupnorm
* [What] Rename original layernorm into layernorm2d
[Why] Prepare to add groupnorm using layernorm5d
* clang-format
* Add groupnorm test
* Refine error message
* Add groupnorm ckProfiler
* Test groupnorm kernel from device_instance
* update example
* upadte profiler
* Fix test naming
* Fix argc number
* Move descriptor and sweeponce to argument for quick debugging
Co-authored-by: Chao Liu <chao.liu2@amd.com>
* add padding algo for bmm+scale+softmax+bmm. Version for verification
* remove verification code
* remove comments
* add padded bmm scale softmax bmm example
* format
* refactor
* add comments for usages of padding bmm+scale+softmax+bmm
Co-authored-by: Chao Liu <lc.roy86@gmail.com>
* Add int4 example for convnd_fwd_bias_relu_add
* Fix AddReluAdd for building without int4 support
* Update CMakeLists.txt
* Format
* Convert int4 tensors for int8 kernel
* Fix device memory allocation
* Format
* Format
* Add custom target to bundle examples together
* Add int4 example conditionally (just copy from int8 example)
* Extract common code into common.hpp
* Move ref gemm type alias into data-type-specific sources
* Add #error directive to prevent compile with wrong setting
* Let AddAddFastGelu support int4 parameter type
* Let check_err() support int4 parameter type
* Add wrapper function to hide value conversion while copying memory
* Finish int4 example for GEMM + AddAddFastGelu
* Add new DeviceMem API to copy memory
* Use new DeviceMem API to implement examples
* Fix wrongly use of macro 'CK_EXPERIMENTAL_BIT_INT_EXTENSION_INT4'
* Revert "Add new DeviceMem API to copy memory"
This reverts commit e26e7af71e.
* Add conversion ctor for Tensor<>
* Add 'const' specifier to Tensor<>::CopyAsType()
* Convert Tensor<> values before/after transfer between host & device
* Introduce int4 data type.
* Add unit-tests for int4
* Compile int4 UT only when int4 enabled.
* clang-format
Co-authored-by: Adam Osewski <aosewski@amd.com>
* Implement multiple-reduction in one kernel (kernels, device ops, examples)
* Add generic elementwise kernel and device interface
* Add generator for normal-distributed data initialization
* Add host refer implementation of batchnorm-forward and batchnorm-infer
* Add examples for implementing batchnorm-forward and batchnorm-infer using generic kernels
* Remove un-needed including in batchnorm example
* Renaming generic_elementwise to elementiwise in kernel and device classes/functions
* Change in gemm_layernorm examples to use DeviceElementwise instead of Device5AryElementwise
* Change in exampe 19_binary_elementwise to use DeviceElementwise instead of DeviceBinaryElementwise
* Change in device_cgemm_4gemm_xdl_cshuffle.hpp to use kernel_elementwise instead of kernel_binary_elementwise
* Add DeviceElementwiseBase and use it in device_normalize_instance.cpp
* Removing and renaming files
* Update to synchronize gemm_layernorm client example to the generic element-wise device op API
* Update to synchronize with the latest headers directory and HostTensorDescriptor interface renaming
* Merge two static member functions in device_elementwise.hpp
* Remove unary_elementwise_1d kernel and device
