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pthread linking errors on SLES. 

Adds a pass to fuse pointwise operators into one "pointwsie" op that has a submodule which does the calculation.

Designed to allow a user to format the values needed for the json_string: migraphx::operation("reduce_mean", "{axes : [%i, %i, %i, %i]}", axes[0], axes[1], axes[2], axes[3]) instead of needing to use string concat or stringstream

Enable a cppcheck rule to catch these redundant casts in the future

Added features:
This enables wrapping each migraphx operator with rocTX markers.
It adds new knob trace to migraphx-driver binary.

Limitation:

rocTX standalone does not output a file, it needs to be used with rocprof. Example command line:

/opt/rocm/bin/rocprof -i ./in.txt --hip-trace --roctx-trace --flush-rate 10ms --timestamp on -d cagri_out --obj-tracking on /opt/rocm/bin/migraphx-driver trace ./resnet50-v2-7.onnx --onnx --gpu
Co-authored-by: Shucai Xiao <shucai@gmail.com>

Inverse of DepthToSpace op
Co-authored-by: Shucai Xiao <shucai@gmail.com>

 when running a model on GPU, migraphx tries to print out content from gpu memory, which causes a segfault. The solution is to copy the gpu memory content back to CPU before the print.

This PR is for the nonzero operator with static output shape.  
Co-authored-by: Paul Fultz II <pfultz2@yahoo.com>
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

Previously dot operator was defined as C = alpha * A . B + beta * C where * is scalar multiplication and . is dot product or matrix multiplication depending on dimension of the inputs.

Aim is to have the definition of dot operator as C = A . B without having alpha or beta.

In order to achieve the same effect as alpha and beta (1) it multiplies the one of the inputs to the dot operator with alpha value. (2) if beta is present then, multiplies the C with beta and then adds into the output from step 1.

Add multinomial op to onnx parser with ref and GPU implementations.

The onnx parser inserts a literal of shape {batch_size, sample_size} with random values in the range [0, 1) and inserts existing ops to compute the cumulative density function. The multinomial operator multiplies the random values by the sum of the CDF and returns the index of the first element of the CDF that is greater than the result, representing samples randomly drawn from [0, class_size) that follow the log-probability distribution.

Resolves #821
Co-authored-by: Shucai Xiao <shucai@gmail.com>

Add RandomNormal, RandomNormalLike, RandomUniform, and RandomUniformLike to onnx parser and onnx tests

Each pair of Random*/Random*Like is implemented using a single op_parser because the ops share the same essential attributes and algorithm with the difference that Random*Like get the output type and/or shape from an input argument and Random* take both from attributes.

Resolves #907
Resolves #959

Supports 1,11,13 ONNX Operator Set

Checks wavefront size, then changes implementation and number of threads for DPP reduce

Add forward compatibility support for compile options 

Needed to bypass passes when fusing pointwise operators into a module.

This reverts commit 9e43cb8b.

This PR aims to remove alpha and beta attributes from dot operator completely.

Previously dot operator was defined as C = alpha * A . B + beta * C where * is scalar multiplication and . is dot product or matrix multiplication depending on dimension of the inputs.

Aim is to have the definition of dot operator as C = A . B without having alpha or beta.

In order to achieve the same effect as alpha and beta (1) it multiplies the one of the inputs to the dot operator with alpha value. (2) if beta is present then, multiplies the C with beta and then adds into the output from step 1.

make file_options struct an opaque object for ABI compatibility, uses make generate to auto-generate and includes  modified tests.
Co-authored-by: Paul Fultz II <pfultz2@yahoo.com>

Add Loop operator for opset version 13.
Notes: 1) Default max iteration number is 10 if no max iteration number is provided
2) To change the max iter number, a user can set the max_loop_iterations in the onnx_option struct when parsing a model.
3) The returned shape of the scan output is from the max_loop_iterations even the actual loop num is less than that. This issue also applies to other operators like NonZero and NonMaxSuppression. A issue #948 is created to track this and to be resolved later.
Co-authored-by: Paul <pfultz2@yahoo.com>
Co-authored-by: mvermeulen <5479696+mvermeulen@users.noreply.github.com>

Assert shapes dont change
Co-authored-by: Shucai Xiao <Shucai.Xiao@amd.com>

Add ability to parse ThresholdedRelu ONNX operator.

Resolves #888
Co-authored-by: Shucai Xiao <shucai@gmail.com>

Add operators, refactor parsers, add rewrite passes, add tests
Add ref implementations
Move broadcasting of scales and zero points to onnx parser
Allow for x and zero_point to have different types in quantizelinear; fix zero_point default type
fp16 and fp8 quantization to include subgraph and parameters
fix unit test to use qdq operators for int8 quantization
Co-authored-by: turneram <alturner@amd.com>

Improve check_context to handle submodules better
Co-authored-by: Shucai Xiao <shucai@gmail.com>

* Add module pass manage

Implement the Where operator for the CPU and GPU.  This is for better performance.