* try to run commavq
* fix 0 dim, start implementing new ops
- Implement EmbedLayerNormalization
- Implement Attention
* SkipLayerNormalization and FastGelu
* use original torch model, cast inputs
* fix some ops:
- properly do Cast
- Attention: bi- and unidirectional
- FastGelu: add bias before gelu
* cleanup onnx_ops.py
* add validation option to benchmark
* cleanup imports
* add checks incase onnx2torch implements ops in future
* run onnx instead of original torch
* just skip gpu on m1
* reactivate the other models
* check for strange params & squash whitespace
* cleanup
* fix causal mask Attention
* Range doesn't need int cast
* embedding vocab_counter same dtype as input
* no need to cast
* always validate, fix PosixPath ort
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Co-authored-by: George Hotz <george@comma.ai>
