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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

Added new random_seed op and some tests.  New ref_ops_test rand_uniform_and_seed_test tests random_seed and rand_uniform together as a set.

* 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

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.

Added dynamic input handling to multinomial.hpp.  Tests don't pass because it still requires both a random uniform, and dynamic-friendly prefix_scap operations to accept dynamic inputs

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

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

* 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

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

Relies on Removed split_single_dyn_dim compile flag #1711
Exposes dynamic_dimension as a opaque object with dynamic_dimensions and optimals
Exposes ONNX dyn_input_dims and default_dyn_dim to run with dynamic batch
Updates api.py to be able to create objects from aggregate initialization (used for dynamic_dimension)
Uses offload copy for now

Makes the optimals into a std::set<std::size_t>
Changes shape object functions to handle the opts change
Changes to convolution, flatten, pooling, and convolution in that they no longer calculate the output optimal dimensions. Instead returns empty opts. Will need to change this in the future if we want to support dynamic shapes fully.
Many changes to tests and shape calls with respect to the new optimals

Adds a new GPU compiler pass split_single_dyn_dim that handles when one input parameter has a single non-fixed dynamic_dimension.
commonly occurs for dynamic batch or BERT sequence length
Splits the dynamic shape into several submodules will static input parameters to handle all of the cases in the dynamic_dimension range.
Essentially does what I manually did for the select_module verify tests
Adds a compile option split_single_dyn_dim that toggles the pass on/off. Defaults to false.
Updates verify_program.hpp and run_verify.cpp to allow for the tests to change the compile_options