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Use this call to also skip converts when running a simplify_algebra pass over a program.

Allows us to not throw warnings instead of using [[maybe_unused]] flag instead.

Adds this to handle broadcasted values instead of just scalars

Used to avoid the case where  1e-12 is used and is matched as zero errornously resulting in removing the call with the incorrect value.

Throw an exception when this occurs to indicate our simpliciation passes resulted in a singularity somewhere. Related to #1236

Simplify addition zero multiplication and divide operations. Added approrpiate test cases with returns and replacing the instruction and operand to just return zero.

Using the unit/neg unit matchers to handle subtraction operations in the same steps. Added unit tests for both cases.

Part of changes that go wtih #1236. Reverts -1 divide operations to a simple negation of the parameter

Add handling for zero addition operations into the find_unit_ops() matcher functor.

Added test case and code to simplify zero additions between paremeters and literals during simplifications.  In reference to issue #1236

Simplfies our code for all operations and reusing original unit tests for overalpping matcher.

Done to satisfy simplifications specified by #1236 .  Just replace every  parameter divided by 1 with itself. It's assumed that the eliminate_identity() pass will handle generated identity operators in our run_pass()

Save a multiply operation with that of a negation of  input parameter x. Suggested improvement via #1236

Commit for the day, work in progress as I'm failing one of our unit tests outside of the change

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>

prioritizing int8 over int8x4 when it is applicable
Amend return to continue in apply loop
Adding error handling in case int8x4 compilation failed
Co-authored-by: Paul Fultz II <pfultz2@yahoo.com>

Break up the gpu::code_object  print to show the actual kernels...

gpu::code_object::add_kernel: 0.646121ms, 5%
gpu::code_object::mul_kernel: 0.623822ms, 5%
gpu::code_object::add_mul_erf_add_mul_mul_kernel: 0.498902ms, 4%
gpu::code_object::mul_add_kernel: 0.478352ms, 4%