GitLab

Was debugging/ trying to figure out why indexing was incorrect. Used a bunch of
prints and such.

These work in tandem to create a shape via the calculate strides() call. Seemed
to introduce more issues than fix, since we don't have access to resize()

Right now this is cleanup but I had used rev_partial_sum and the multiplies()
template operator created in algorithm to achieve this during debugging for
gather. The idea here would be we would statically create array() with calculate_strides()
to fix the empty stride dimensions.

Was added to implement calculate strides() for array creation via shape() but
needed to use forward iterators instead since we didn't implement reverse iterators.

Removing since it's not needed but could be used still if needed.

This was added during debugging when attempting to add in partial_sum()
to replicate device behavior when using calculate_strides(). In this case
this isn't needed

This is needed to get multi(i) below to work correctly when indexing.

Originally thought this was with the output_t.

Tried to get a proper templated shape of out_comp but right now this
seems to break as I can't just update the length of a shape and get a proper
output of the strides. Currently this breaks/asserts.

I think this is the cause of axis > 0 failing since we're not getting proper gathering
for the other axes as a result and get repeated rows with the wrong data.

Generates output from the given onnx description of gather found here:
https://github.com/onnx/onnx/blob/main/docs/Operators.md#gather

Using this as a baseline as I seem to pass on the zero case but fail on the
axis = 1 case. In the other tests of shape (3,3) there appears to be a similar
error when axis = -1 which after tuning is axis = 1.

Test if symmetry of the data matrix has any bearing on how the gather operation
produces valid output between ref and jit implimentations

tests negative index handling for scalar index input
Signed-off-by: Ted Themistokleous <ted.themistokleous@amd.com>

test for negative index for single item tensor

Currently failing negative indices and negative axis tests.

All others "seem" to work

Noticed an oddball case that the cases that fail pass, if the sizes of a dimension
of a container is even instead of odd...

The purpose of this test is to try axis dimensions of even dimension values
to determine if the same negative axis as the test_gather_neg_axis sees changes
in gather. In this case a pass should match ref.

Add stride based multi-index similar to device functions. Between the device
gather and what's available for jit it looks like we're using lens instead of
strides to calculate indicies.

Seems to fix the 1d case of indices for this jit gather.

Should be able to test a mix of both indices for gather output

Currently fails this jit model but useful for coverage

Pair programming with Paul

Taken from gatherND.cpp and modified so we include the axis parameter as opposed
to the batch_dims attribute.

Should always exist since we default this to zero when no axis is provided from
the instruction

Work in progress for the .hpp jit side.

HIP had change in previous rocm releases to use --offload-arch instead of --cuda-gpu-arch.

This should be backwards compatbile. hipRTC also supports --offload-arch.

Extends dot MIGX operator to handle dynamic input shapes
Only allow dot between two dynamic shapes that have exactly matching outer dimensions
Inner dimensions must also match correspondingly
Updates dot related tests
Change check_shapes to use shape.ndim()
ONNX parsers for GEMM and MatMult will be updated in a separate PR

No major changes required, use dyn_output and pass dynamic shape when calling compute_shape()
Adds dynamic shape tests

Changes flatten's compute_shape() to handle dynamic shapes
Calculates the flattened shape with the min, max, and opt

Currently, quantizing a program with rnn layers to fp16 results in segmentation faults due to a "convert" operation being applied to an "undefined" instruction.

The following changes are implemented to fix this issue:

Added is_undefined method to the instruction class that returns true if all inputs to the instruction are from an undefined op.
Updated rewrite_rnn pass to use the new is_undefined method rather than checking ins->name()
Updated the dead_code_elimination pass to also use this new method rather than only checking the instruction name

* Add implicit_conversion

Extends the Argmax operator to handle dynamic input shapes.
Only shape function changes

Need this for when we debug and use MIGRAPHX_TRACE_EVAL() to show tuples
Without this we break when reading our buffer due to the use of visit()
This came up as part of #1283 debugging.

Extends unsqueeze and squeeze to work for dynamic input shapes
Does not handle the steps parameter
Adds some additional negative axes shape tests

Update dialect registration interface
Update 2nd build pipeline call and use full arch name

Fix problem with the contiguous operator constructing non-standard shape literals.  A non-standard literal will almost never be used, since a literal is known at compile time.  Added some comments on the intended behavior:

- literal{shape, vector} constructor with a non-standard shape is intended to keep the same ordering as the given vector. The data buffer will be populated such that when the non-standard indexing is used the original order is as given.
- literal{shape, argument} constructor directly copies the data buffer from the argument
- Changed non-standard literal fill() to use tensor_view iterators as it handles non-standard shapes now
- Changed the contiguous ref_ops_test to be more helpful

Extends the pooling operators for dynamic shape inputs

AveragePooling
GlobalAveragePooling
MaxPooling
GlobalMaxPooling
LpNormPooling
GlobalLpNormPooling
y.github.com>

Bumps [tensorflow](https://github.com/tensorflow/tensorflow) from 2.7.2 to 2.9.3.
- [Release notes](https://github.com/tensorflow/tensorflow/releases)
- [Changelog](https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md)
- [Commits](https://github.com/tensorflow/tensorflow/compare/v2.7.2...v2.9.3

)

---
updated-dependencies:
- dependency-name: tensorflow
  dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Chris Austen <causten@users.noreply.github.com>

Merging #1391 caused an extra adjust allocation pass for GPU targets. This removes that merge error.

Extends ref transpose operator for dynamic shapes
Make dynamic tests more consistent naming

* Default ROCm version set to 5.3 and schedule update due to DST for nightly build.

Disabling it untill int8 fix is in mainline from MIOpen and also so that QA tests could run migraphx-driver and unittests from MIGraphX.

Fix to stop types failing for logical_xor during our fusions. 

Extends the ref contiguous operator to handle dynamic shapes
Updates the eliminate_contiguous pass to use the dyn_output struct