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Makes a version of allocate that takes in dimensions and allocates a buffer
Going to create a simplify_dynamic_ops compiler pass that will use the use_shape_attr flag
The ONNX op ConstantOfShape needs the buffer to be filled with a specific value, so going to make another PR for that and a fill operator

Re-organizes ref tests to improve the speed of compilation 

Adds support for dynamic input shape in pooling operator along with auto-padding. This combination requires that the padding (and therefore the output shape) can't be computed until runtime.

Allows slice to work with variable starts, ends, and axes input
Outputs a dynamic shape even with a static shape data input when the starts and ends are variable

This PR constitutes the MIGraphX-side changes needed to not break the build in the presence of
ROCmSoftwarePlatform/rocMLIR#1136 , and updates what data is sent in to MLIR during the kernel generation and tuning process.

* add quant_dot fusion, clip literal opt

* 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

* Add initial tuning support

* Format

* Add extra param

* Format

* Use exauhstive flag

* Format

* Set expected shapes

* Format

* Format

* Fix missing symbol

* Format

* Add missing license header

* Format

* Update src/targets/gpu/include/migraphx/gpu/mlir.hpp

* 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.

* rename function 'near' to 'make_near'

* try disabling vega10 machine

* 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

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.

Fixes #1746

BatchNorm only has x as the runtime input parameter for the following equation. All the other parameters are compile-time constants and related operations can be const-folded before quantizing to fp16 to preserve precision.

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

The find_reshaper is supposed to do this, but it doesnt work and there were no tests. So I updated for it to work and I added unit tests for it.

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.