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Currently, while copying a host buffer to the device, it first registers/maps the host buffer pointer to address space of the device.

If the host buffer has been allocated by the hipHostMalloc then, it is implicitly registered to the device's address space, and no need to register again. This PR adds a check for the same.

Gives better clarity to which argument is throwing an error, especially in cases with nested IF statements in the network.

instancenorm parser always creates literal of type float which would fail in type check while creating binary ops if model is fp16.

* Add in changes for onnx Mod operator

Initial operator for mod implementation and test cases for integer and floating based types.

Need to use fmod from stdlib for floating point types. half_float::half thankfully is specced to the use the existing std::fmod() call when looking at the half.hpp implementation.

fmod_flag should mirror the onnx fmod attribute. Right now using a floating point type without setting that on the user side to true will result in an exception.

Ref ticket #1283 

* Add is_supported to the target
* Add get_target_assignments
* Rename assignment to target_assignments
* Add ref target header to test
* Add fpga target
* Make context const in compute

C++ API is not printing thrown exception string. this improves on it.

Dynamic shape handling in shape object

Bug 1: create_literal was using back_inserter to copy vector with already allocated size, causing double the size of literal.
Fix 1 : not use back_inserter
Bug 2: Input param to model can be from operation that has multiple output, in that case name of the input param would contain : e.g. input_1:0
Fix 2: Look for : and take substring

Depends on #1199

Adds ONNX parser functionality for dynamic input shapes.
Uses options parameter in parse_onnx()

Changes to operator includes:

removed some includes that were not used
included argument.hpp where clang-tidy wanted it

Reduce header inclusion in op headers

This will ensure that migraphx.h can be included from a C compiler, and check that the C API can be called. This includes stdbool.h which is needed when using bool from C.

* Only run __syncthreads when there is data to preload
* Improve loops
* Add const attribute to improve optimizations

Show the number of operators and per operator avg time in summary...

Summary:
gpu::gemm: 8.738ms / 73 = 0.119699ms, 64%
gpu::triadd_layernorm: 0.831381ms / 24 = 0.0346409ms, 7%

Improve the assembly dump to track where certain instruction come from.

Added is_supported and get_target_assignments methods to the target and program, respectively, to eventually support multi-target compilation and execution.

Initial sketch for changes to shape to handle dynamic dimensions

Instead of just unsqueezing to an axis of 1 a step can be set to use instead. So instead of unsqueezing {3, 12} to {3, 1, 12} a step of 2 will unsqeeze to {3, 2, 6} instead

*In the verification tests, check that saving and reloading the program is the same program. This also fixes serialization to always load instructions in the same order. There is also fixes for deconv and quant_conv which didn't save the solution id, and was broken for serialization.

* Add softmax kernel

This reorders the transposes across slice to improve horizontal fusion for contiguous. This also improves eliminate_contiguous to remove contiguous better across splits.

* Add mlir c api

* Formatting

* Create a type attribute

* Formatting

* Parse module

* Formatting

* Add mlir dump function

* Add test case

* Formatting

* Fix tidy issues

* Update mlit version

* Update to newer mlir

* Format

* Move mlir to the gpu and update the test

* Formatting

* Fix bug when appending module

* Format

* Remove old cmake flag

* Update message

* Add return

* Format

* Add mlir_compile

* Format

* Register dialect

* Handle unsinged integers

* Dont provide output for return instruction

* Format

* Add code to insert memrefs

* Format

* Add mlir verification

* Formatting

* Enable pointwise_fusion

* Disable eliminate_data_type

* Set kernal name

* Format

* Fix device name

* Formatting

* Fix output arg

* Format

* Updates

* Upate hash

* Add fuse_mlir pass

* Format

* Add fuse mlir

* Format

* Update mlir

* Sort parameter names

* Format

* Reenable disabled passes

* Remove old mlir conv

* Remove asym default padding

* Add more verbose tracing

* Format

* Fix compilation errors

* Format

* Whitelist operators

* Format

* Add namespace

* Format

* Update triple

* Format

* Use func dialect

* Format

* Use func.return

* Format

* Upgrade mlir version

* Add comment

* Handle symetrical padding

* Format

* Cleanup debug output

* Format

* List failed tests

* Move mlir compile to jit pipeline

* Format

* Update version

* Add source locations

* Format

* Correctly add module

* Format

* Update failed tests

* Fix failures when mlir is disabled

* Format

* Update mlir version

* Check type for fp32

* Format

* Remove failed test

* Update mlir in driver

* Tidy fixes

* Foramt

* Tidy fixes

* Format

* Fix const

* Remove from requirements

* Fix cmake version

* Fix tidy warning

* Use another ifdef

* Fix tidy

* Other tidy fix

* Format

* Update hash

* Add missing license files

* Format

* Format

* Fix fnction name

This is an extension to insert_module_instructions, but instead of just inserting from a module, it can insert a range or a vector of instructions.

Allows PyTorch converted version of SSD-resnet34 to work

 Compiles significantly faster than constructing all the objects. It also reduces recompiles as well.

* Add function to get a module tree
* Get parent module in the pass manager

One-line fix to register the op miopen_fusion. This error was causing loading of compiled model files (*.mxr) to fail.

* Jit contiguous

Adds compute_method for the experimental custom ops.
Adds a test for the same using HIP APIs.
Depends on #1183
Solves #1101

* remove eliminate workspace
* remove sync device and other tags

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

* Fixing misspelled macro
Co-authored-by: Paul Fultz II <pfultz2@yahoo.com>

* remove code for allocation of C param in dot lowering

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

* [#935] Update tf_parser to have add_common_op() for parse_relu6

Similar to that of the onnx_parser.cpp add a add_common_op template and functionality to support clip based operations. This is done so clip operations can be guarenteed to have the same dimensions.

* fixup! [#935] Update tf_parser to have add_common_op() for parse_relu6

* fixup! fixup! [#935] Update tf_parser to have add_common_op() for parse_relu6

* fixup! fixup! fixup! [#935] Update tf_parser to have add_common_op() for parse_relu6

* fixup! fixup! fixup! fixup! [#935] Update tf_parser to have add_common_op() for parse_relu6

* Formatting

* fixup! Formatting
Co-authored-by: Umang Yadav <29876643+umangyadav@users.noreply.github.com>
Co-authored-by: Paul Fultz II <pfultz2@yahoo.com>

* add allocate op header

* formatting

* add replace_allocate pass

* formatting

* move output param to remove_allocate pass

* formatting

* fix bugs in replace_allocate pass

* formatting

* fix verify if tests

* formatting

* move if op logic

* formatting

* cleanup lowering

* cleanup lowering

* formatting

* fix tidy

* formatting

* fix tidy

* add cpu allocate check

* formatting

* change cpu allocate in pass

* formatting

* add some tests for replace_allocate pass

* formatting

* pass by ref

* fix run_pass

* formatting

* update variable name for module

* update dce to use contains() and fix tidy

* formatting

* update cppcheck

* add if test

* formatting

* add if test

* rename var to mod_output_names

* formatting

* remove conditional

* update allocate op and tests

* formatting

* update replace_allocate tests

* update create_output_names() and conditional in replace_allocate

* formatting

* remove extra variable in replace_allocate

* update tools script for allocation_model
Co-authored-by: Umang Yadav <29876643+umangyadav@users.noreply.github.com>
Co-authored-by: Chris Austen <causten@users.noreply.github.com>
Co-authored-by: Paul Fultz II <pfultz2@yahoo.com>

* Use custom distance function

* Pass module, skip order check if other module

* Change other valid()

* Remove unnecessary declaration

* test multiple module dependency

* Refactor to make more clear

* Code cleanup

* Simplify fix

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

Consolidate the vectorize and preload
Add vectorization to reduction
Co-authored-by: kahmed10 <15948690+kahmed10@users.noreply.github.com>