* [ONNX] Allow specifying only a subset of input/output names
Then we can only specify the "real" names while ignoring the names for all the parameters
* fix
* Update utils.py
* Workaround in onnx to get transposes into init_nets
This adds a pass to ONNX so that it can speculate Transpose
operators so that ONNX's split pass can put them into an init_net
Also fixes a potential bug in onnx peephole where an optimization
across blocks might move a Value and violate scoping.
* Perform shape propagation when embedding a program into a trace.
This ensures the trace still has type information specific to that trace, which will help onnx export succeed in more cases.
* Codemod to update our codebase to 0.4 standard
* Update some of the test scri[ts
* remove Variable in test_clip_grad_value
* fix _symbolic_override_wrapper_maker
* Switch JIT passes to take a graph rather than TracingState
* Add pybind11 binding for ONNX pass from graph
* Fix canonicalize pass
* address comment
* Switch ToONNX to explicitly return new graph
* optimize_graph instead of optimize_trace
Allows you to export an ONNX model as:
Protobuf file (this is what we have now)
Uncompressed zip archive
Compressed zip archive
Directory
* Experimental support for different ONNX export types
* Remove a copy
* Add comment
* Add test cases
* lint
* fix bug
* address comments
* Namespaced symbols
- Our interned strings now have structure, "ns::symname" rather than just
"symname" before. We support efficient namespace testing for uniques
by encoding the namespace in one byte in the Symbol internal representation.
See torch/csrc/jit/interned_strings.h for a more in-depth implementation
discussion.
- All uses of ksymbol are now attr::symbol (or some appropriate namespace).
The valid namespaces are prim, attr, onnx and aten.
- Symbol is bound in Python as a qualified string "attr::symbol", EXCEPT for the
attribute setting/getting API, whose symbols must always be attr
symbols; they get special cased to assume strings are passed.
There's a little bit of naughtiness in the implementation, maybe you know
how to solve it.
- However, the g.op() convenience function assumes that you're generating
ONNX operators, unless you explicitly qualify.
- All ATen operators and nodes have built-in interned strings generated
for them, so you should never have to write a string literal ever again.
The tracing code is adjusted to use it.
- ONNX exporter now properly tests to see that all operators are in
onnx namespace before accepting the export. This is way more
robust than the previous exporter, which would be willing to
export capitalized operators which were not actually ONNX operators.
- A slight organizational change for symbolic.py; this module now ONLY
contains aten operators. In particular, the exporter for Constant
has moved into utils.py (along with Undefined, from the C++ side),
since primitive ops get "special treatment."
- The un-inplacing logic in recording is more robust, so that we don't
delete a trailing underscore from __and__. This never affected us
before because we didn't have any tests for it.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
