## `VariableTracker::build()` hides the Builders
### The problem
In the current code, creating a `VariableTracker` involves choosing one of two `Builder` classes and either calling a method, or calling a constructor that creates an object that you immediately call, [like this](083c9149b7/torch/_dynamo/variables/functions.py (L761-L768)).
Variations on this code are repeated in many places.
More, the `Builder` classes have a lot of dependencies, so they have to be loaded late in the whole import process to avoid circular imports, so they end up being repeatedly imported at local scope.
### The solution
In this commit, the import from `builder` and the logic of choosing and calling the Builder class are hidden in a single static factory method, `VariableTracker.build()`, easier to reason about and to import.
This commit net lowers the total lines of code by over 150 lines by removing repetitive logic and unnecessary local imports.
**CHANGES:** Originally the name of the static method was `VariableTracker.create()` but a static method on a derived class, `LazyVariableTracker.create()` now exists with a different signature that's irreconcilable, so the new static method was renamed to `VariableTracker.build()`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/135714
Approved by: https://github.com/jansel
Fixes an issue where if the context arg is not provided, Dynamo would throw an arg mismatch error.
The skips are there because Dynamo would previously fall back to eager on those tests due to the arg mismatch error.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/137809
Approved by: https://github.com/drisspg
See `test_inline_closure_returned_by_another_function_and_captures` and #136814 for more context.
In #90286, we introduced an optimization so that for captured cells that are unmodified during a Dynamo trace, `UserFunctionVariable` will represent them as variable of the cell's actual value, rather than a `NewCellVariable`.
Later on we introduced more mechanisms to model such cells across function calls (#104222), and across function calls where `NestedUserFunctionVariable::bind_args` need to look up further in the parent frames (#106491) to find these cells' values.
This patch removes `InlinedClosureVariable` in favor of a simpler modelling, which is also more consistent with what was introduced in #90286, i.e., just model these cells as their contents, in `symbolic_locals`.
This fixes#136814 because resolution of `InlinedClosureVariable` to the underlying cell content value happens in
`NestedUserFunctionVariable::bind_args`, which requires Dynamo to have the value in scope at the function call site (when Dynamo does inlining), but's not always the case (as the test case shows). However, if we model the cells in `symbolic_locals`, we never need such resolution, and the values are directly stored into the `NestedUserFunctionVariable::closure` upon the function creation, at which point Dynamo always has the cell value in `symbolic_locals` for look up.
Fixes#136814.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/137510
Approved by: https://github.com/williamwen42
Moves `TransformGetItemToIndex` to a file where dynamo stores other traceable HOP concepts. (We don't trace through torch.* modules by default)
Tracing through the mode required fixing a bug in dynamo autograd function, which fixed a graph break, which caused the autograd test failures (skipping for now and will file an issue)
Previously those tests were in essence running in eager, because dynamo would fallback due to an arg mismatch error.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/137120
Approved by: https://github.com/yanboliang
ghstack dependencies: #137114, #137115, #137116, #137117
Changes:
1. Move `polyfill.py` -> `polyfills/__init__.py`. It can be used as `polyfill.xxx` -> `polyfills.xxx`.
2. Move submodule loading from `polyfills/__init__.py` to `polyfills/loader.py`.
Merge `polyfill.py` and `polyfills/` packages. Each polyfill module have its own namespace for better code organization.
The ultimate goal is make `polyfills/__init__.py` empty and all polyfill functions move to its own namespace.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/133977
Approved by: https://github.com/jansel
Fixes the observed graph breaks in https://github.com/pytorch/pytorch/issues/121349 and https://github.com/pytorch/pytorch/issues/121350.
But there are still graph breaks since a random output is being used as a seed, e.g.
```python
import random
import torch
def fn(x):
seed = random.randint(0, 100)
rand = random.Random(seed)
return x + rand.randrange(10)
opt_fn = torch.compile(fn, backend="eager", fullgraph=True)
opt_fn(torch.ones(1))
```
fails with
```
torch._dynamo.exc.InternalTorchDynamoError: UnspecializedPythonVariable() is not a constant
```
when tracing the line
```
rand = random.Random(seed)
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/133725
Approved by: https://github.com/jansel
Significant bytecode generation API change!
The new suggested convention to generating bytecode to call a function is now to wrap instructions that push a callable to the stack with `add_push_null`, then that callable is called with `create_call_function` with `push_null=False` (see diff for examples).
In Python 3.13, NULL is now expected to be pushed after the callable. In <=3.12, the NULL was pushed before the callable. This change abstracts away the exact placement of the NULL, but the developer must be aware that a NULL may be needed when codegen'ing a callable.
This abstraction also reduces the need for the `push_null=True` option in `create_call_function`, which removes the need to rotate a NULL to the right place on the stack with a sequence of `SWAP` instructions.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/129172
Approved by: https://github.com/jansel
Adds support for `Variable._execution_engine.queue_callback()`, which is used in FSDP2.
Important tests:
- `pytest -rA test/inductor/test_compiled_autograd.py::TestCompiledAutograd::test_callback_graph_break_throws_error`
- `pytest -rA test/inductor/test_compiled_autograd.py::TestAutogradWithCompiledAutograd::test_callback_adds_callback`
- `PYTORCH_TEST_WITH_DYNAMO=1 python test/test_autograd.py -k TestAutograd.test_callback_adds_callback`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/126366
Approved by: https://github.com/xmfan
