Automatically generate operator tests (#2754)

Summary:
Pull Request resolved: https://github.com/pytorch/executorch/pull/2754

## Context

One of the most time consuming parts of adding new operators is writing tests to verify that the implementation is correct. This changeset introduces a codegen solution for automatically generating tests. The goal is to introduce a simple interface to specify what inputs an operator should be checked with, and have a 1 button solution for generating the code and executing operator tests.

## Usage Overview

From the developer's perspective, they only need to interact with `op_tests/cases.py`. The file is very simple:

```
# Prime numbers dim sizes for testing
XL = 113
L = 89
M2 = 41
M1 = 37
M = 29
S2 = 11
S1 = 7
S = 5
XS = 3

...

def get_mm_inputs():
    return [
        ((M1, L), (L, M2)),
        ((S1, S2), (S2, M)),
    ]

test_cases = {
    "aten.add.Tensor": get_binary_elementwise_inputs(),
    "aten.sub.Tensor": get_binary_elementwise_inputs(),
    "aten.div.Tensor": get_binary_elementwise_inputs(),
    "aten.mul.Tensor": get_binary_elementwise_inputs(),
    "aten.mm.default": get_mm_inputs(),
}
```

It just contains a mapping from the name an operator is registered under in the operator registry to a list of inputs for which tests should be generated.

To generate and run tests:

```
buck run //xplat/executorch/backends/vulkan/test/op_tests:compute_graph_op_tests_bin
```

## Design Overview

The code generation is mostly built on top of [torchgen](https://github.com/pytorch/pytorch/tree/main/torchgen), which is PyTorch's codegen system for parsing [native_function.yaml](https://github.com/pytorch/pytorch/blob/main/aten/src/ATen/native/native_functions.yaml) and generating C++ ATen functions from it. The basic idea is:

1. Using the operator registry name, find the corresponding native function for native_function.yaml
2. Use the function schema from the parsed native function to generate test fixtures that can build a Vulkan compute graph for the operator
3. Individual test cases can be generated by creating ATen tensors and calling the ATen operator to get a reference output, then using the test fixture to get a Vulkan output and compare it to the reference output.
4. GTest [test parameterization](https://github.com/google/googletest/blob/main/googletest/samples/sample8_unittest.cc) is used to test each test case under a combination of dtypes, storage types, and memory layout

[Example generated cpp](https://www.internalfb.com/phabricator/paste/view/P1202279441)

Reviewed By: copyrightly

Differential Revision: D55446638

fbshipit-source-id: 93ca8e7cd43cee1e2678c489d6f2227507ef256f