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Handles all 4 Fp8 dtypes listed here : https://onnx.ai/onnx/technical/float8.html
Follows saturation/clipping logic from table there as well : https://onnx.ai/onnx/technical/float8.html#cast
Only adding fp8e4m3fnuz in MIGraphX IR for now.

let the user know which targets migraphx was built for and how to build migraphx for their gpu.

Enable with MIGRAPHX_ENABLE_CK=1 and --exhaustive-tune tune flag

Co-authored-by: Paul Fultz II <pfultz2@yahoo.com>

Updates the hip::copy_to_gpu and hip::copy_from_gpu operators to work with dynamic shapes

Allows for offload_copy to be used with dynamic batch

Changed assert in select_module because the argument might now be smaller with how offload_copy will work with dynamic batch. (maximum buffer size will be used)

* deprecate HCC

Added CMakeFlag for hipRTC. MIGRAPHX_USE_HIPRTC.
Added stages in Jenkins for hipRTC.
Fixes for some of the pending issues from hipRTC.

* Remove device functions
* Update tests

Using not and or improves readability. The cppcheck rule will help ensure we are doing it consistently.

Updated each source file in the repo with the existing license.

When create a tensor_view with vector date type, the last dimension of the shape should be divided by the vec_size.

Add exclusive and reverse modes to gpu implementation of prefix_scan_sum, which completes support for ONNX op CumSum

change max number of groups in a kernel to 1B for greater performance

Update the base version of clang-format from 5.0 to 10.0

Changed the number of threads in a block from 256 to 128
Increased the max number of blocks in the kernel from 256 to 1M.
For the case that the axis is the last dimension, we removed the computation of index since it is not required.

With these change, we can get about 2x speedup compared to the develop branch for the softmax op used in the BertSquad model.

This PR is for the nonzero operator with static output shape.  
Co-authored-by: Paul Fultz II <pfultz2@yahoo.com>
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

Add multinomial op to onnx parser with ref and GPU implementations.

The onnx parser inserts a literal of shape {batch_size, sample_size} with random values in the range [0, 1) and inserts existing ops to compute the cumulative density function. The multinomial operator multiplies the random values by the sum of the CDF and returns the index of the first element of the CDF that is greater than the result, representing samples randomly drawn from [0, class_size) that follow the log-probability distribution.

Resolves #821
Co-authored-by: Shucai Xiao <shucai@gmail.com>

Checks wavefront size, then changes implementation and number of threads for DPP reduce

Add Loop operator for opset version 13.
Notes: 1) Default max iteration number is 10 if no max iteration number is provided
2) To change the max iter number, a user can set the max_loop_iterations in the onnx_option struct when parsing a model.
3) The returned shape of the scan output is from the max_loop_iterations even the actual loop num is less than that. This issue also applies to other operators like NonZero and NonMaxSuppression. A issue #948 is created to track this and to be resolved later.
Co-authored-by: Paul <pfultz2@yahoo.com>
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

Implement the Where operator for the CPU and GPU.  This is for better performance.

* add topk operator doe ref, cpu and gpu
* Hash modules for quicker lookup of modules
* add onnx unit test
* add unit tests for the topk operator
Co-authored-by: Paul <pfultz2@yahoo.com>
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

* check for divisor encodable or not, fallback if needed

* verify test for retinaface case

* Add initial scan operator

* Formatting

* Fix with a working test

* Fix bugs

* Formatting

* Formatting

* Simplify

* Formatting

* Use non-power of 2 for test

* Make pointer
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

* init reverseOp branch: ref op + ref test. WIP

* first passing basic test

* cleanup

* additional axis implementation

* additional test

* ref op implementation vec to int for axis

* ref op test change for axis

* initial gpu files and test

* updates to implementation and test

* fixed some issues

* clang format

* cleanup

* formatting

* removing comments

* remove local size, back to default

* update tests: replace with std functions

* multiple axis for reverse op

* fix a build error

* clang format

* more tests

* fix a bug for the reverse device function

* clang format

* fix a bug

* clang format

* ref test updates, multiaxis

* formatting
Co-authored-by: Shucai Xiao <Shucai.Xiao@amd.com>
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

* Remove unused data types

* Formatting

* Reduce types generated for hip kernels

* Formatting

* Fix onnx tests

* Formatting
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>