Summary:
This commit adds the ability to insert a node with inputs, using the schema to check the inputs are valid types, fill in any default values, and perform standard implicit conversions. Since it is schema based, it will discover and use the right overload.
Constructors to `NamedValue` enable it to be constructed using `IValue` constants so it is possible to use constant values in the input list as well:
```
g.insert(aten::add, {v, 3});
```
Keyword arguments are also supported:
```
g.insert(aten::add, {v}, {{"other", t}, {"scalar", 1}});
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10198
Differential Revision: D9307252
Pulled By: zdevito
fbshipit-source-id: 644620aa85047d1eae1288383a619d50fec44d9b
Summary:
More clang tidy cleanups in `torch/csrc`. This time:
1. `hicpp-use-equals-default` recommends `= default` instead of `{}` for constructors/destructors. This is better practice because it expresses the intent better (https://stackoverflow.com/questions/6502828/what-does-default-mean-after-a-class-function-declaration)
2. `readability-inconsistent-declaration-parameter-name` enforces that parameter names in the declaration match parameter names in the definition. This is just generally useful and can prevent confusion and bugs.
Also updated my script a little bit.
apaszke ezyang
Pull Request resolved: https://github.com/pytorch/pytorch/pull/9737
Differential Revision: D9069069
Pulled By: goldsborough
fbshipit-source-id: f7b3f3a4eb4c9fadc30425a153566d3b613a41ae
Improve script builtin checking using schema
* This add aten_schema.h which provides a barebones amount of type and
argument information about each builtin operator
* emitBuiltinCall is updated to use this information rather than
aten_dispatch to ensure the operator is correct.
* handling of keyword and position arguments now matches python behavior
* There is no longer a requirement that kwargs be constant or that the
attributes of an op must be entirely constant or non-constant
* compiler now constructs a non-attributed version of the op first and
then turns it into the constant-attribute version if all attributes
are constants.
* default arguments for builtins now work
* SugaredValue::call and similar functions now have SourceRange information
for their arguments so that error reporting is more accurate
Notes:
* This does not try to merge the builtin checking with python arg parser.
Given that we will eventually have C10 schema which will replace aten_schema,
we will eventually have a C++ description of the schema and working of that
description directly will be the easiest form to understand.
* python function calls and script method calls do not support keyword arguments yet.
When we add this support we should refactor the handling in tryEmitSchema
that resolves keywords into a common function.
* default arguments work
* keyword arguments to builtins work (still need to extend to calling python and other script methods)
* much better error reporting for incorrect builtins
Lift any constants to attributes on nodes when possible
* Schema is usable internally in the compiler as
the function signatures of script functions as well as for builtin
operators.
* Adds a List[T] class to better represent the arguments to cat/stack
as a type rather than with custom checking.
* Support kwargs for calls of script methods
A future commit will be needed to add support for:
* calls to script _functions_ which are currently are GraphExecutors without schema info.
* kwargs to python functions, which will require refactoring python op
* Allow `__constant__` values in a ScriptModule to be used as attributes for builtin functions
* Fix bugs in @script loops
1. while loops run shape propagation multiple times until the shapes have converged.
There were two bugs here. (a) First the 'changed' condition was not checking if it actually
changed the output, and instead would mark changed = true if the two inputs were different.
This incorrect because the output of the block and the input of the block may always have different shapes.
Now it actually checks if it is about to change the output entry that it is writing to.
(b) expand nodes were being inserted into the graph even inside the while loop body. However, if
we iteratively discover that the input shape to one of these expands is actual dynamic, then
it was incorrect to insert the expand in the first place. This changes it so that we only insert expands
after we have converged on the shapes.
2. the way deleteExtraInputs removed loop-carried dependencies was unsafe because it would lookup
Value* elements in the loop body's environment that were previously invalidated when deleteExtraInputs
remove another input to the loop. This changes the way deleteExtraInputs works so that it never has to
read a value out of the loop body's environment to avoid using the invalidated pointers.
* Support list and tuple literals: Adds support for [a, b], (a, b) and "a, "
* Allow non-tensors to reach emitBuiltinCall, each SugaredValue::call
is now responsible for checking the types of its inputs.
Add support for calling cat with a tuple to emitBuiltinOp
This modifies the registration process so that all script methods
in a ScriptModule are defined at once.
Method gains a `method_creator` callback that gets invoked when the
method is first called to define it if it has not already been defined.
Recursive cycles in this `method_creator` are checked.
This approach was chosen over first creating all the graphs and then
inlining the call sites because it will combine better with type
propagation for non-tensor types like tuples. e.g.
```
a = foo(b)
return bar(*a)
```
* Allow tuples to be re-assigned
This commit improves our support of tuples by making them more first-class.
In particular, it allows tuples to be re-assigned across loops and ifs.
It does this by making them first-class values in the Graph IR, and then
removing the tuples in a LowerTuples pass.
An alternative approach would have added more support for desugaring tuples
in the Environment object as they were emitted. Instead,
the current approach was chosen anticipating a future when tuples are
fully supported (including the interpreter). In that future, the current
code can be completly reused with the LowerTuples pass just becoming
a optimization that removes unneeded tuple allocations.
* Fixes to the way script handles multiple values, and other minor fixes.
This commit improves our handling of operators that return multiple values.
Builtins are now checked so that they return the right number of values,
and support for TupleValue is extended to all things that can return
multiple values.
This resolves issues where the compiler accepted things like:
a, b = c + c
This would cause the interpreter to crash. Now each operator knows
how many results it will produce and can check it against the number
of requested inputs.
Notes:
* Allow True/False literals in constant expressions
* make handling of keyword constants more consistent to support True/False
* make parsing constants match the way we construct constants from python
* improve the error messages when accessing bad graph attributes.
* switch findTensorOp to return an optional.
* check that attribute types are correct in findTensorOp
* Check the correct number of outputs for builtins
This also changes emitExpr to return a single SugaredValue
Rather than possibly returning multiple values, emitExpr now
always returns a single value, which _might_ be a tuple. This approach
more closely follows python making the code easier to follow.
Checks for returning the right number of values are now located in
the assignment operator, and occur when unpacking the tuple.
We still pass `n_binders` to function calls so that calls into python
know how many values they should return.
* Something that works
* Tuple sugared value
* Works with commenting out input size check
* support string frontend
* Initial starred assignment
* Fix parser
* Fixup tests
* clang-format
* fix rebase error
* lint
* move star assign test to string frontend to make py2 happy
* Py2 fix: parse starargs from Call node
* Address some comments
* Fixup merge
* Remove overloaded unary operators
* Bugfix and test case
* Address a few more comments
* asValues -> asTuple
* Remove unrolledFor stuff
* Fixup getValues
* Pass CallsiteDescriptor struct and have different behavior for different call types
* Address comments and lint
* some type checks
* Address comments
* lint
* Fix mistake
Like `__slots__` the `__constants__` property changes the set/getattr behavior of a script module for the keys listed so they behave as constants.
This enables script methods to use them in way that are otherwise not allowed.
* Python numbers/bools can be inlined as constants in script code.
* List of numbers can be iterated over using for loops
* nn.ModuleLists can be used in for loops as well, unrolling their content.
* Have ScriptModule inherit from Module
This is accomplished by created replacement _parameters, _buffers,
and _modules which implement the OrderedDict APIs but which
actually get/set their members inside script::Module
* Merge TracedModule with ScriptModule
* Move logic of attribute handling into Python bindings rather than
make script::Module handle it. This was redundant with nn.Module,
which already handles attribute.
* Make TracedModule a subclass of ScriptModule
* Move handling of attribute kind logic into bindings.
* Allow ScriptModule to contain non-script module submodules.
Add script::Module C++ class to represent script modules
switch AST -> IR conversion to work on Modules/Methods rather than raw graphs
function-only AST -> IR conversion is just a simplified case where there is
only one module with a single method and no parameters.
introduce SugaredValue in compiler.h to represent values in scope in a script
function that are not first-class and that get desugared. This is used to
represent the module's self parameter, as well as python function calls,
and method calls on tensor
provide a Python ScriptModule that provides a nice API on top of script::Module
allowing for the definition of script modules with methods, parameters,
and submodules
Not in this PR but intended for the future:
ScriptModule actually subclasses nn.Module, with most methods implemented
Unification of tracedmodule and script module functionality into one container class.
Detailed changelog:
* Switch compiler over to using Module, but don't
use them yet.
* Remove intermediate attribute encoding in compiler
* Create SugaredValue object to handle resolution
of compiled module.
* switch to_ir to modules, implement Select
* hacky python wrappers
* Private ScriptModule
* Add `define` to script module
* Attributes use TK_LIST_LITERAL
this anticipates adding a real list literal expression to the language.
* Add a metaclass to make sure script stubs are registered
* Add a test
* Doc createResolutionCallback
* Docs and minor editing
* Address PR comments
* Document
* Fix unicode issue
This PR adds the possibility to build the C++ parts of autograd and jit, with no dependency on Python.
The goal is to allow taking a PyTorch IR representation (a tree s-expr) and running it with provided inputs.
Prerequisite: build PyTorch so that codegen runs once.
Instructions:
cd tools/cpp_build
bash build_all.sh
This will build libtorchjit and torchjit_test in tools/cpp_build/build/torchjit-build. The latter basically runs the code in test_jit.cpp for now.
While writing the PR, it turned out that a few of Python.h includes were redundant. They were removed here (PyTorch tests still pass on my machine, we'll see CI).
* Introduce Python-free builds of autograd and jit
* Remove NO_PYTHON ifdef in functions/special
* Add Python function calls to script
* Script compiler gains a `Resolver` object that runs when it does not understand a function call. This decouples the python resolution from the conversion to IR.
* torch.jit.trace annotation now creates a GraphExecutor
The other torch.jit.trace, which was used for testing purposes and for onnx to get the trace graph, is now called torch.jit. torch.jit.get_trace_graph.
* @script annotation, and compilation unit for strings
Additionally:
- add support for calling functions that are not methods in the Python frontend
- add an end-to-end test for the Python frontend
- add a capture_stdout helper for checking that `print` actually works
