8000 update test files by youkaichao · Pull Request #88 · thuml/depyf · GitHub
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youkaichao merged 2 commits into from
Oct 8, 2025
+13,771 −24,555
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update test files #88

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d8498d8
update test files
youkaichao Oct 8, 2025
dd8aefc
update test files
youkaichao Oct 8, 2025
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38 changes: 29 additions & 9 deletions ...debug_function_aot_eager_with_dynamic_shape_with_grad/__compiled_fn_1.Backward_graph.0.py
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Expand Up @@ -2,19 +2,39 @@
import torch
from torch import device
class GraphModule(torch.nn.Module):
def forward(self, primals_1: "f32[10]", tangents_1: "f32[10]"):
def forward(self, primals_1: "f32[10]", primals_2: "f32[10]", sum_1: "f32[]", tangents_1: "f32[10]"):
# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:4 in toy_function, code: x = a / (torch.abs(a) + 1)
neg: "f32[10]" = torch.ops.aten.neg.default(tangents_1)
abs_1: "f32[10]" = torch.ops.aten.abs.default(primals_1)
add: "f32[10]" = torch.ops.aten.add.Tensor(abs_1, 1); abs_1 = None
div_1: "f32[10]" = torch.ops.aten.div.Tensor(primals_1, add)
div_2: "f32[10]" = torch.ops.aten.div.Tensor(div_1, add); div_1 = None
mul: "f32[10]" = torch.ops.aten.mul.Tensor(neg, div_2); neg = div_2 = None
div_3: "f32[10]" = torch.ops.aten.div.Tensor(tangents_1, add); tangents_1 = add = None
div: "f32[10]" = torch.ops.aten.div.Tensor(primals_1, add)

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:6 in toy_function, code: return x * b
mul_2: "f32[10]" = torch.ops.aten.mul.Tensor(tangents_1, div)

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: b = b * -1 + b.sum()
mul: "f32[10]" = torch.ops.aten.mul.Tensor(primals_2, -1); primals_2 = None
add_1: "f32[10]" = torch.ops.aten.add.Tensor(mul, sum_1); mul = sum_1 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:6 in toy_function, code: return x * b
mul_3: "f32[10]" = torch.ops.aten.mul.Tensor(tangents_1, add_1); tangents_1 = add_1 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: b = b * -1 + b.sum()
sum_2: "f32[]" = torch.ops.aten.sum.default(mul_2)
expand: "f32[10]" = torch.ops.aten.expand.default(sum_2, [10]); sum_2 = None
mul_4: "f32[10]" = torch.ops.aten.mul.Tensor(mul_2, -1); mul_2 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: b = b * -1 + b.sum()
add_2: "f32[10]" = torch.ops.aten.add.Tensor(expand, mul_4); expand = mul_4 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:4 in toy_function, code: x = a / (torch.abs(a) + 1)
neg: "f32[10]" = torch.ops.aten.neg.default(mul_3)
div_2: "f32[10]" = torch.ops.aten.div.Tensor(div, add); div = None
mul_5: "f32[10]" = torch.ops.aten.mul.Tensor(neg, div_2); neg = div_2 = None
div_3: "f32[10]" = torch.ops.aten.div.Tensor(mul_3, add); mul_3 = add = None
sgn: "f32[10]" = torch.ops.aten.sgn.default(primals_1); primals_1 = None
mul_1: "f32[10]" = torch.ops.aten.mul.Tensor(mul, sgn); mul = sgn = None
mul_6: "f32[10]" = torch.ops.aten.mul.Tensor(mul_5, sgn); mul_5 = sgn = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:4 in toy_function, code: x = a / (torch.abs(a) + 1)
add_1: "f32[10]" = torch.ops.aten.add.Tensor(div_3, mul_1); div_3 = mul_1 = None
return (add_1, None)
add_3: "f32[10]" = torch.ops.aten.add.Tensor(div_3, mul_6); div_3 = mul_6 = None
return (add_3, add_2)

12 changes: 8 additions & 4 deletions .../debug_function_aot_eager_with_dynamic_shape_with_grad/__compiled_fn_1.Forward_graph.0.py
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Expand Up @@ -8,8 +8,12 @@ def forward(self, primals_1: "f32[10]", primals_2: "f32[10]"):
add: "f32[10]" = torch.ops.aten.add.Tensor(abs_1, 1); abs_1 = None
div: "f32[10]" = torch.ops.aten.div.Tensor(primals_1, add); add = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: if b.sum() < 0:
sum_1: "f32[]" = torch.ops.aten.sum.default(primals_2); primals_2 = None
lt: "b8[]" = torch.ops.aten.lt.Scalar(sum_1, 0); sum_1 = None
return (lt, div, primals_1)
# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: b = b * -1 + b.sum()
mul: "f32[10]" = torch.ops.aten.mul.Tensor(primals_2, -1)
sum_1: "f32[]" = torch.ops.aten.sum.default(primals_2)
add_1: "f32[10]" = torch.ops.aten.add.Tensor(mul, sum_1); mul = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:6 in toy_function, code: return x * b
mul_1: "f32[10]" = torch.ops.aten.mul.Tensor(div, add_1); div = add_1 = None
return (mul_1, primals_1, primals_2, sum_1)

32 changes: 23 additions & 9 deletions ...ut/debug_function_aot_eager_with_dynamic_shape_with_grad/__compiled_fn_1.Joint_graph.0.py
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@@ -1,7 +1,7 @@
from __future__ import annotations
import torch
from torch import device
class joint_helper(torch.nn.Module):
class inner_f(torch.nn.Module):
def forward(self, primals, tangents):
primals_1: "f32[10]"; primals_2: "f32[10]"; tangents_1: "f32[10]";

Expand All @@ -11,20 +11,34 @@ def forward(self, primals, tangents):
add: "f32[10]" = torch.ops.aten.add.Tensor(abs_1, 1); abs_1 = None
div: "f32[10]" = torch.ops.aten.div.Tensor(primals_1, add)

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: if b.sum() < 0:
# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: b = b * -1 + b.sum()
mul: "f32[10]" = torch.ops.aten.mul.Tensor(primals_2, -1)
sum_1: "f32[]" = torch.ops.aten.sum.default(primals_2); primals_2 = None
lt: "b8[]" = torch.ops.aten.lt.Scalar(sum_1, 0); sum_1 = None
add_1: "f32[10]" = torch.ops.aten.add.Tensor(mul, sum_1); mul = sum_1 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:6 in toy_function, code: return x * b
mul_1: "f32[10]" = torch.ops.aten.mul.Tensor(div, add_1)
mul_2: "f32[10]" = torch.ops.aten.mul.Tensor(tangents_1, div); div = None
mul_3: "f32[10]" = torch.ops.aten.mul.Tensor(tangents_1, add_1); tangents_1 = add_1 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: b = b * -1 + b.sum()
sum_2: "f32[]" = torch.ops.aten.sum.default(mul_2)
expand: "f32[10]" = torch.ops.aten.expand.default(sum_2, [10]); sum_2 = None
mul_4: "f32[10]" = torch.ops.aten.mul.Tensor(mul_2, -1); mul_2 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: b = b * -1 + b.sum()
add_2: "f32[10]" = torch.ops.aten.add.Tensor(expand, mul_4); expand = mul_4 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:4 in toy_function, code: x = a / (torch.abs(a) + 1)
neg: "f32[10]" = torch.ops.aten.neg.default(tangents_1)
neg: "f32[10]" = torch.ops.aten.neg.default(mul_3)
div_1: "f32[10]" = torch.ops.aten.div.Tensor(primals_1, add)
div_2: "f32[10]" = torch.ops.aten.div.Tensor(div_1, add); div_1 = None
mul: "f32[10]" = torch.ops.aten.mul.Tensor(neg, div_2); neg = div_2 = None
div_3: "f32[10]" = torch.ops.aten.div.Tensor(tangents_1, add); tangents_1 = add = None
mul_5: "f32[10]" = torch.ops.aten.mul.Tensor(neg, div_2); neg = div_2 = None
div_3: "f32[10]" = torch.ops.aten.div.Tensor(mul_3, add); mul_3 = add = None
sgn: "f32[10]" = torch.ops.aten.sgn.default(primals_1); primals_1 = None
mul_1: "f32[10]" = torch.ops.aten.mul.Tensor(mul, sgn); mul = sgn = None
mul_6: "f32[10]" = torch.ops.aten.mul.Tensor(mul_5, sgn); mul_5 = sgn = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:4 in toy_function, code: x = a / (torch.abs(a) + 1)
add_1: "f32[10]" = torch.ops.aten.add.Tensor(div_3, mul_1); div_3 = mul_1 = None
return pytree.tree_unflatten([lt, div, add_1, None], self._out_spec)
add_3: "f32[10]" = torch.ops.aten.add.Tensor(div_3, mul_6); div_3 = mul_6 = None
return pytree.tree_unflatten([mul_1, add_3, add_2], self._out_spec)

10 changes: 7 additions & 3 deletions ..._grad/__compiled_fn_1.Captured_Graph.0.py → ...244fc238_4ca7_4b9a_b98e_572d4a04df3c.0.py
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Expand Up @@ -11,8 +11,12 @@ def forward(self, L_a_: "f32[10]", L_b_: "f32[10]"):
add: "f32[10]" = abs_1 + 1; abs_1 = None
x: "f32[10]" = l_a_ / add; l_a_ = add = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: if b.sum() < 0:
# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: b = b * -1 + b.sum()
mul: "f32[10]" = l_b_ * -1
sum_1: "f32[]" = l_b_.sum(); l_b_ = None
lt: "b8[]" = sum_1 < 0; sum_1 = None
return (lt, x)
b: "f32[10]" = mul + sum_1; mul = sum_1 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:6 in toy_function, code: return x * b
mul_1: "f32[10]" = x * b; x = b = None
return (mul_1,)

10 changes: 7 additions & 3 deletions ...rred_runtime_asserts___compiled_fn_1.0.py → ...a2554e37_9a0b_4f28_be48_1203ba14091b.0.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,8 +11,12 @@ def forward(self, L_a_: "f32[10]", L_b_: "f32[10]"):
add: "f32[10]" = abs_1 + 1; abs_1 = None
x: "f32[10]" = l_a_ / add; l_a_ = add = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: if b.sum() < 0:
# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: b = b * -1 + b.sum()
mul: "f32[10]" = l_b_ * -1
sum_1: "f32[]" = l_b_.sum(); l_b_ = None
lt: "b8[]" = sum_1 < 0; sum_1 = None
return (lt, x)
b: "f32[10]" = mul + sum_1; mul = sum_1 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:6 in toy_function, code: return x * b
mul_1: "f32[10]" = x * b; x = b = None
return (mul_1,)

10 changes: 7 additions & 3 deletions ..._grad/__compiled_fn_1.Captured_Graph.0.py → ...a600377f_6d52_48df_b307_ce01bd20b9f1.0.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,8 +11,12 @@ def forward(self, L_a_: "f32[10]", L_b_: "f32[10]"):
add: "f32[10]" = abs_1 + 1; abs_1 = None
x: "f32[10]" = l_a_ / add; l_a_ = add = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: if b.sum() < 0:
# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: b = b * -1 + b.sum()
mul: "f32[10]" = l_b_ * -1
sum_1: "f32[]" = l_b_.sum(); l_b_ = None
lt: "b8[]" = sum_1 < 0; sum_1 = None
return (lt, x)
b: "f32[10]" = mul + sum_1; mul = sum_1 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:6 in toy_function, code: return x * b
mul_1: "f32[10]" = x * b; x = b = None
return (mul_1,)

10 changes: 7 additions & 3 deletions ...rred_runtime_asserts___compiled_fn_1.0.py → ...244fc238_4ca7_4b9a_b98e_572d4a04df3c.0.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,8 +11,12 @@ def forward(self, L_a_: "f32[10]", L_b_: "f32[10]"):
add: "f32[10]" = abs_1 + 1; abs_1 = None
x: "f32[10]" = l_a_ / add; l_a_ = add = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: if b.sum() < 0:
# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: b = b * -1 + b.sum()
mul: "f32[10]" = l_b_ * -1
sum_1: "f32[]" = l_b_.sum(); l_b_ = None
lt: "b8[]" = sum_1 < 0; sum_1 = None
return (lt, x)
b: "f32[10]" = mul + sum_1; mul = sum_1 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:6 in toy_function, code: return x * b
mul_1: "f32[10]" = x * b; x = b = None
return (mul_1,)

22 changes: 22 additions & 0 deletions ...insert_deferred_runtime_asserts___compiled_fn_1_a2554e37_9a0b_4f28_be48_1203ba14091b.0.py
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@@ -0,0 +1,22 @@
from __future__ import annotations
import torch
from torch import device
class GraphModule(torch.nn.Module):
def forward(self, L_a_: "f32[10]", L_b_: "f32[10]"):
l_a_ = L_a_
l_b_ = L_b_

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:4 in toy_function, code: x = a / (torch.abs(a) + 1)
abs_1: "f32[10]" = torch.abs(l_a_)
add: "f32[10]" = abs_1 + 1; abs_1 = None
x: "f32[10]" = l_a_ / add; l_a_ = add = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: b = b * -1 + b.sum()
mul: "f32[10]" = l_b_ * -1
sum_1: "f32[]" = l_b_.sum(); l_b_ = None
b: "f32[10]" = mul + sum_1; mul = sum_1 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:6 in toy_function, code: return x * b
mul_1: "f32[10]" = x * b; x = b = None
return (mul_1,)

22 changes: 22 additions & 0 deletions ...insert_deferred_runtime_asserts___compiled_fn_1_a600377f_6d52_48df_b307_ce01bd20b9f1.0.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,22 @@
from __future__ import annotations
import torch
from torch import device
class GraphModule(torch.nn.Module):
def forward(self, L_a_: "f32[10]", L_b_: "f32[10]"):
l_a_ = L_a_
l_b_ = L_b_

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:4 in toy_function, code: x = a / (torch.abs(a) + 1)
abs_1: "f32[10]" = torch.abs(l_a_)
add: "f32[10]" = abs_1 + 1; abs_1 = None
x: "f32[10]" = l_a_ / add; l_a_ = add = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: b = b * -1 + b.sum()
mul: "f32[10]" = l_b_ * -1
sum_1: "f32[]" = l_b_.sum(); l_b_ = None
b: "f32[10]" = mul + sum_1; mul = sum_1 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:6 in toy_function, code: return x * b
mul_1: "f32[10]" = x * b; x = b = None
return (mul_1,)

32 changes: 23 additions & 9 deletions ...tion_aot_eager_with_dynamic_shape_with_grad/__compiled_fn_1.tensorify_python_scalars.0.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
from __future__ import annotations
import torch
from torch import device
class joint_helper(torch.nn.Module):
class inner_f(torch.nn.Module):
def forward(self, primals, tangents):
primals_1: "f32[10]"; primals_2: "f32[10]"; tangents_1: "f32[10]";

Expand All @@ -11,20 +11,34 @@ def forward(self, primals, tangents):
add: "f32[10]" = torch.ops.aten.add.Tensor(abs_1, 1); abs_1 = None
div: "f32[10]" = torch.ops.aten.div.Tensor(primals_1, add)

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: if b.sum() < 0:
# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: b = b * -1 + b.sum()
mul: "f32[10]" = torch.ops.aten.mul.Tensor(primals_2, -1)
sum_1: "f32[]" = torch.ops.aten.sum.default(primals_2); primals_2 = None
lt: "b8[]" = torch.ops.aten.lt.Scalar(sum_1, 0); sum_1 = None
add_1: "f32[10]" = torch.ops.aten.add.Tensor(mul, sum_1); mul = sum_1 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:6 in toy_function, code: return x * b
mul_1: "f32[10]" = torch.ops.aten.mul.Tensor(div, add_1)
mul_2: "f32[10]" = torch.ops.aten.mul.Tensor(tangents_1, div); div = None
mul_3: "f32[10]" = torch.ops.aten.mul.Tensor(tangents_1, add_1); tangents_1 = add_1 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: b = b * -1 + b.sum()
sum_2: "f32[]" = torch.ops.aten.sum.default(mul_2)
expand: "f32[10]" = torch.ops.aten.expand.default(sum_2, [10]); sum_2 = None
mul_4: "f32[10]" = torch.ops.aten.mul.Tensor(mul_2, -1); mul_2 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:5 in toy_function, code: b = b * -1 + b.sum()
add_2: "f32[10]" = torch.ops.aten.add.Tensor(expand, mul_4); expand = mul_4 = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:4 in toy_function, code: x = a / (torch.abs(a) + 1)
neg: "f32[10]" = torch.ops.aten.neg.default(tangents_1)
neg: "f32[10]" = torch.ops.aten.neg.default(mul_3)
div_1: "f32[10]" = torch.ops.aten.div.Tensor(primals_1, add)
div_2: "f32[10]" = torch.ops.aten.div.Tensor(div_1, add); div_1 = None
mul: "f32[10]" = torch.ops.aten.mul.Tensor(neg, div_2); neg = div_2 = None
div_3: "f32[10]" = torch.ops.aten.div.Tensor(tangents_1, add); tangents_1 = add = None
mul_5: "f32[10]" = torch.ops.aten.mul.Tensor(neg, div_2); neg = div_2 = None
div_3: "f32[10]" = torch.ops.aten.div.Tensor(mul_3, add); mul_3 = add = None
sgn: "f32[10]" = torch.ops.aten.sgn.default(primals_1); primals_1 = None
mul_1: "f32[10]" = torch.ops.aten.mul.Tensor(mul, sgn); mul = sgn = None
mul_6: "f32[10]" = torch.ops.aten.mul.Tensor(mul_5, sgn); mul_5 = sgn = None

# File: /Users/youkaichao/data/DeepLearning/depyf/tests/test_pytorch/test_pytorch.py:4 in toy_function, code: x = a / (torch.abs(a) + 1)
add_1: "f32[10]" = torch.ops.aten.add.Tensor(div_3, mul_1); div_3 = mul_1 = None
return pytree.tree_unflatten([lt, div, add_1, None], self._out_spec)
add_3: "f32[10]" = torch.ops.aten.add.Tensor(div_3, mul_6); div_3 = mul_6 = None
return pytree.tree_unflatten([mul_1, add_3, add_2], self._out_spec)

18 changes: 0 additions & 18 deletions ...ebug_function_aot_eager_with_dynamic_shape_with_grad/__compiled_fn_11.Backward_graph.0.py
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15 changes: 0 additions & 15 deletions ...ebug_function_aot_eager_with_dynamic_shape_with_grad/__compiled_fn_11.Captured_Graph.0.py
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