Summary:
Based on discussions with Sherlock + Zhengxu in D51118067, updated the internal thrift schema to match the OSS schema.
Verifier failures:
* Test contains a None as input, resulting in no meta["val"]
* Test contains torch.autograd.grad_mode.set_grad_enabled as an op, which also results in no meta["val"]
* torch.autograd.grad_mode.set_grad_enabled is also not a valid op
* Test adds a "parameter" to the state dict but the parameter is not an nn.Parameter, causing an assertion failure
So to bypass these failures I did the following hacks(?):
* Before creating the exported program in deserialization, populate nodes w/o meta["val"] with meta["val"] = None
* Add torch.autograd.grad_mode.set_grad_enabled to the skip opset
* Duplicated ExportGraphSignature into aot_export.py so that the graph signature checks will be skipped
Configerator changes in D51343615
Test Plan: CI
Reviewed By: zhxchen17
Differential Revision: D51342921
Pull Request resolved: https://github.com/pytorch/pytorch/pull/113810
Approved by: https://github.com/zhxchen17
Summary: yolo fixing issues. See Test plan
Test Plan:
buck2 run 'fbcode//mode/dev' fbcode//executorch/examples/portable/test:test_export -- -r test_mv3_export_to_executorch
[Need acl to repro this but the error message looks straight forward]
buck2 test 'fbcode//mode/dev-nosan' fbcode//pye/model_inventory/nlu_stella_cap:nlu_stella_cap_test -- --exact 'pye/model_inventory/nlu_stella_cap:nlu_stella_cap_test - test_export_to_backend_dynamic_quantized (pye.model_inventory.nlu_stella_cap.NluStellaCapTest.NluStellaCapTest)'
Differential Revision: D51128480
Pull Request resolved: https://github.com/pytorch/pytorch/pull/113296
Approved by: https://github.com/tugsbayasgalan
Summary: Turn on verifier check for exportec program ctor. Note that this effectively detect a large surface of spec violations, so we also spend some time fixing them one by one in this diff.
Test Plan: CI
Differential Revision: D51014944
Pull Request resolved: https://github.com/pytorch/pytorch/pull/113075
Approved by: https://github.com/angelayi
A resubmit of https://github.com/pytorch/pytorch/pull/108447. Copy over the descriptions:
This is a follow-up of the discussion in https://github.com/pytorch/pytorch/pull/108356, where we want to repalce source_fn with source_fn_stack
Before this PR, for the following example:
```python
backend = EagerAndRecordGraphs()
@torch.compile(backend=backend, fullgraph=True)
def cond_f(pred, pred2, x, y):
def true_fn(pred2, x, y):
return x + y
def false_fn(pred2, x, y):
def true_fn2(x, y):
return x.sin() - y.cos()
def false_fn2(x, y):
return x.cos() - y.sin()
return control_flow.cond(pred2, true_fn2, false_fn2, (x, y))
return control_flow.cond(pred, true_fn, false_fn, (pred2, x, y))
```
The graph captured is shown below:
```python
class GraphModule(torch.nn.Module):
def forward(self, L_pred_ : torch.Tensor, L_pred2_ : torch.Tensor, L_x_ : torch.Tensor, L_y_ : torch.Tensor):
l_pred_ = L_pred_
l_pred2_ = L_pred2_
l_x_ = L_x_
l_y_ = L_y_
cond_true_1 = self.cond_true_1
cond_false_1 = self.cond_false_1
cond = torch.ops.higher_order.cond(l_pred_, cond_true_1, cond_false_1, [l_pred2_, l_x_, l_y_]); l_pred_ = cond_true_1 = cond_false_1 = l_pred2_ = l_x_ = l_y_ = None
return (cond,)
class GraphModule(torch.nn.Module):
def forward(self, l_pred2_, l_x_, l_y_):
add = l_x_ + l_y_; l_x_ = l_y_ = None
return add
class GraphModule(torch.nn.Module):
def forward(self, l_pred2_, l_x_, l_y_):
cond_true_0 = self.cond_true_0
cond_false_0 = self.cond_false_0
cond = torch.ops.higher_order.cond(l_pred2_, cond_true_0, cond_false_0, [l_x_, l_y_]); l_pred2_ = cond_true_0 = cond_false_0 = l_x_ = l_y_ = None
return cond
class GraphModule(torch.nn.Module):
def forward(self, l_x_, l_y_):
sin = l_x_.sin(); l_x_ = None
cos = l_y_.cos(); l_y_ = None
sub = sin - cos; sin = cos = None
return sub
class GraphModule(torch.nn.Module):
def forward(self, l_x_, l_y_):
cos = l_x_.cos(); l_x_ = None
sin = l_y_.sin(); l_y_ = None
sub = cos - sin; cos = sin = None
return sub
```
the source_fn for inner cond, sin, cos will be a (name, target) tuple:
```
('cond', <torch._ops.HigherOrderOperator object at xxx>)
('sin', 'sin')
('cos', 'cos')
('sub'. <built-in function sub>)
```
After this pr, the source_fn_stack will be a list of (name, target) tuple. The bottom of stack is the end of the list.
```
[('cond', <torch._ops.HigherOrderOperator object at xxx>), ('cond', <torch._ops.HigherOrderOperator object at xxx>)],
[('cond', <torch._ops.HigherOrderOperator object at xxx>), ('cond', <torch._ops.HigherOrderOperator object at xxx>), ('sin', 'sin')],
[('cond', <torch._ops.HigherOrderOperator object at xxx>), ('cond', <torch._ops.HigherOrderOperator object at xxx>), ('cos', 'cos')]
[('cond', <torch._ops.HigherOrderOperator object at xxx>), ('cond', <torch._ops.HigherOrderOperator object at xxx>), ('sub', <built-in function sub>)]
```
Test Plan:
See added tests in test_higher_order_ops.py and modify existing test.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/108595
Approved by: https://github.com/angelayi, https://github.com/zou3519
Summary: Forward fix t53725825. New map implementation breaks multiple internal tests. forward fix it for some of them. To unblock others, mark unfixed ones are expectedFailure first.
Test Plan: Test with CI.
Reviewed By: angelayi
Differential Revision: D46084287
Pull Request resolved: https://github.com/pytorch/pytorch/pull/102009
Approved by: https://github.com/angelayi
