add test_onnx_ops.py (#8569)

* boom

* fix webgpu

* use exact variable names in test so that AI can read easier

* add tag for specific test name like test a specific dtype

* fix ruff

* astype everything

* dtype in array creation

* just arange

* is 67% considered fixed?

* move test up

* small cleanups

* share function

* add qgemm as well

* add qgemm too

* make sure qgemm comes out as int

* take out qgemm for now

* fixed test

* add correct qgemm

* addressing feedback here too, early naive fix for now

* simplify bias and c to be minimalistic enough to test correctness

* refactored qlinearops

* maybe these asserts aren't the best..

* fix test

* updated tests to cover new ops

* try to add to CI

* move test_onnx_ops into testextra/

* more attention tests

* qlinear_add atol=1

* attention still not fullllllly correct

* it is what it is

---------

Co-authored-by: chenyu <chenyu@fastmail.com>

extra/onnx_helpers.py

@@ -16,7 +16,6 @@ def get_example_inputs(graph_inputs:dict[str, OnnxValue]):
 
 def validate(onnx_file, inputs, rtol=1e-5, atol=1e-5):
   run_onnx = OnnxRunner(onnx.load(onnx_file))
-  tinygrad_out = run_onnx(inputs)
 
   ort_options = ort.SessionOptions()
   ort_options.log_severity_level = 3
@@ -26,8 +25,10 @@ def validate(onnx_file, inputs, rtol=1e-5, atol=1e-5):
   out_values = ort_sess.run(out_names, np_inputs)
   ort_out = dict(zip(out_names, out_values))
 
-  assert len(tinygrad_out) == len(ort_out) and tinygrad_out.keys() == ort_out.keys()
+  tinygrad_out = run_onnx(inputs)
+
+  assert tinygrad_out.keys() == ort_out.keys()
   for k in tinygrad_out.keys():
     tiny_v, onnx_v = tinygrad_out[k], ort_out[k]
-    if tiny_v is None: assert tiny_v == onnx_v
+    if tiny_v is None: assert onnx_v is None, f"{k}: {tiny_v=}, {onnx_v=}"
     else: np.testing.assert_allclose(tiny_v.numpy(), onnx_v, rtol=rtol, atol=atol, err_msg=f"For tensor '{k}' in {tinygrad_out.keys()}")