GitLab

* use implicit deps for the sorting
* use BFS for sorting program

* Use shape of Instruction (instead of a default) in add_return()

* Instruction validation fix: not to use a default shape value for comparison

* Fix instruction::replace() to recompute shape for "@return"

* handle the case of missing shape in an Instruction related Test

* use compute_shape() to get op shapes + test case for tuple_type

* add test case shape_test/return_shape_tuple

* Add test for @return to check for half type

* Move @return unit-tests around..; Address review comments

* Broken comparison fix: comparison to a (default) shape of tuple_type

* Test cases: (add) return_shape_empty & (modify) return_shape_tuple

* modify the assert() statement

* Improve performance of pointwise/reduction kernels when using NHWC layouts

* Format

* Add nhwc test

* Format

* Remove inline namespace

* Add reduce test

The --py output can be loaded back in the driver. This will embed the migraphx interperter so we can execute the python directly. There is a migraphx_py library which will dynamically load the version of the library for python version is available on the system.

* Add dynamic input to prefix_scan_op

* Added a shape test.  The op should return the same dynamic shape as the input.

* add 2d shape test for prefix_scan

Throwing on these calls catches dynamic shape errors earlier rather than having to backpedal from a bad call

This adds a format.py file which will check or apply formatting using git clang-format or yapf.

Fixes #1957

Clamping was removed in #1853.

Turns out clamping as necessary to handle overflow/underflow cases. during downcasting, if it overflowed then without clamping it returned infinity.

* add multitarget evaluation
* Add evaluation for the multi-target unit-tests

throw on use_len with non-fixed dynamic dimensions
change normalize_attributes to use input shape rather than input dimensions

Renames deconvolution -> convolution_backwards to be more consistent with the literature
Note: this is not the cross-correlation operator (which is the adjoint of convolution). This is technically a standard convolution operator combined with an upsampling operator rather than a downsampling operator.
Adds unit tests for the padding, strides, dilations, and other op attributes.
Throws on auto_pad attribute since it has not been implemented
Previously it read the attribute and set it but then did nothing with it
Extended for dynamic shapes
Does not support using asymmetric padding (padding_L != padding_R) and output_shape with dynamic shapes.

Changes to the way Pooling operation calculates pooling when there's padding. Old code would clip off any padding values before computing; for instance if an Average pooling window contained 0 1 2 where the 0 is padding, the result was 1.5 instead of 1.0. See Issue 1766

Export API symbols for migraphx, migraphx_ref, migraphx_cpu, migrphx_gpu, migraphx_device, migraphx_tf, and migraphx_onnx. There is a separate PR for migrahx_c.

API symbol exporting affects only Windows. It is transparent on Linux.

This is to help enable multi-target execution. We store a vector of targets and contexts. Currently this will only compile a single target, the PR #1672 is needed to enable multiple targets.

This will also serialize the targets and contexts.

When using the execution_environment or prog.get_context() it will always use the context from the first target assuming this is the "primary" target. Although, its unlikely a user would use execution_environment with a multi-target environment.

Fixes the failing test case in #1815. Added a test that would otherwise fail without the change.

Needed to run multi-targeted program where "main" isn't the only root module. There could be many root modules other than main.

Updates ref version of clip to work with dynamic shapes
Encountered in agentmodel

Fixes #1852  Fixes #1847

* Add trace for SIMPLIFY_ALGEBRA matches

* Fix format

* handle review comments from Umang

-int to size_t for trace
-move env arg to top of simplify_algebra.cpp
-handle overload beter for find_matches

* Rename trace_mod param to trace_pass

More representative naming for what this trace flag does

* Fix convert for the NaNs

* NaNs can't be compared, use std::isnan()

* formatting

* formatting

* formatting

* add extra tests

* initial

* Added tests and new functionality

* Update optimals handling

* Simplify conditionals

* Ref test, update docs

* Remove comment, suggestion unclear

---------
Co-authored-by: Umang Yadav <29876643+umangyadav@users.noreply.github.com>

* fix parse_instancenorm to create broadcast and multibroadcast instructions with two dynamic shape arguments instead of 1.  Their make_op() functions don't support dynamic shapes when called with one input.  This caused an error when parsing an ONNX 3duunet model

* Use add_common_op() to create multibroadcast op.

* add verification and parsing test for instance_norm with dynamic input.  Parse test doesn't pass.

* fix for test; still doesn't pass

* another fix for test; still doesn't pass

* work in progress, instance_norm_dyn_batch_test works but instance_norm_test doesn't

* fix onnx instancenorm tests to match parser changes.  Passes all check tests

* Updated comments explaining usage of add_common_op()

* hand-merged conflicts with develop

* fix instance_norm_half_test after merge

* add Onnx test instance_norm_dyn_batch_half_test

* add shape test cases broadcast_1in_dyn_error and multibroadcast_1in_dyn_error_0

Splits support for using tbb (oneTBB now) between OS's when using
std::execution::par

It appears TBB support seems to wane in earlier versions of g++ in CentOS and
other OS's still require testing/containers to verify builds.

The MIGraphX shim should just operate as normal with copy_if and sort() calls
if TBB support isn't functional for the current OS/g++ version

Also moved the TBB dependency from install_preqs to Ubuntu Docker. Shouldn't breka
other dockers if support isn't added

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

Changed the doc for find_permutation(shape) to be more clear that it is finding the permutation that would make the shape standard

partially solves #1656
This PR only handles compilation part of multitarget.

Move CI to support the rocm5.5 release

Adding support for broadcasted scalars to unsqueeze op.

Specifying steps other than 1 is disallowed in this implementation since we want the output the always be a tensor. We can support varying step sizes if we allow a broadcasted scalar output from this op.

add option to print tf supported ops
sort both onnx and tf ops alphabetically

Exposed the mlir_enabled() call the decide for lowering pipeline's enablement
Disabled the rewrite quantization pipeline in mlir compilation
Added quant convolution as anchor ops
Fixed the return type expectations
Added the fall back hip implementation for quantizelinear and dequantizelinear
Will need advises to improve the implementation for quantizelinear