Update base for Update on "Add ops (addr) | feat(torchlib)"

-----

- Mark nan==nan in assert_close
- Fix aten_isfinite by allowing the exporter to do type promotion according to #563 and introduce `TFloatHighPrecision` for it
- Fix typo in `TRealOrUInt8`

[ghstack-poisoned]

Author: justinchuby

docs/_static/css/custom.css

@@ -1,3 +1,75 @@
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   padding: 4px 0 2px 0;
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+
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+}
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+}
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+}
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+}
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+}
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+}
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docs/articles/2023-06-20-introducing-onnx-script/debugging_screenshot.png

@@ -0,0 +1,7 @@
+# Articles
+
+```{toctree}
+:maxdepth: 1
+
+2023-06-20-introducing-onnx-script/index
+```

docs/articles/2023-06-20-introducing-onnx-script/index.md

@@ -12,7 +12,7 @@
 # -- Project information -----------------------------------------------------
 
 project = "onnxscript"
-copyright = "2023, Microsoft"
+copyright = "Microsoft. All rights reserved."
 author = "onnx"
 version = onnxscript.__version__
 release = version
@@ -38,6 +38,7 @@
 myst_enable_extensions = [
     "amsmath",
     "attrs_inline",
+    "attrs_block",
     "colon_fence",
     "deflist",
     "dollarmath",

docs/articles/2023-06-20-introducing-onnx-script/intellisense_screenshot.png

@@ -96,6 +96,7 @@ result = MatmulAdd(x, wt, bias)
 ```{toctree}
 :maxdepth: 1
 
+articles/index
 tutorial/index
 auto_examples/index
 api/index

docs/articles/2023-06-20-introducing-onnx-script/ten_chunks_model.png

@@ -77,7 +77,9 @@ class TorchLibOpInfo:
     nondeterministic: bool = False
     # Whether the function is designed for complex inputs
     complex: bool = False
-    # The tolerance for the test {dtype: (rtol, atol)}.
+    # The acceptable tolerance of the inference result difference between PyTorch and ORT.
+    # Format: {dtype: (rtol, atol)}.
+    # For example: {torch.float16: (1e-3, 1e-3)}
     tolerance: dict[torch.dtype, tuple[float, float]] = dataclasses.field(default_factory=dict)
     # Expected skips or fails for the test and/or subtests
     skips_or_fails: list[ops_test_common.DecorateMeta] = dataclasses.field(