mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 12:21:27 +01:00
This PR stops `SymNode` from mutating (i.e. simplifying) its expression. Instead, the
simplification (without mutation) is deferred to the `SymNode.maybe_as_int` method.
```python
- FakeTensor(size=(s0,), ...)
- FakeTensor(size=(s1, s2, s3), ...)
- Eq(s0, s1 + s2 + s3)
- FakeTensor(size=(s0,), ...)
- FakeTensor(size=(s1, s2, s3), ...)
```
In summary, this PR:
- Replaces `SymNode._expr` by `SymNode.expr`, removing the old property function
- This makes it so `SymNode` instances never update their expression
- Creates `SymNode.simplified_expr()` method for actually calling `ShapeEnv.replace` on
its expression. Note that this doesn't updates `SymNode.expr`
- Changes how `tensor.size()` gets converted to its Python `torch.Size` type
- Instead of calling `SymInt::maybe_as_int()` method, we create a new
`SymInt::is_symbolic()` method for checking whether it is actually a symbolic value
- This is needed so that when we call `tensor.size()` in the Python side, the returned
sequence is faithful to the actual data, instead of possibly simplifying it and
returning an integer
- 2 files needs this modification:
- _torch/csrc/Size.cpp_: for handling `torch.Tensor.size` Python calls
- _torch/csrc/utils/pybind.cpp_: for handling `symint.cast()` C++ calls
Pull Request resolved: https://github.com/pytorch/pytorch/pull/107492
Approved by: https://github.com/ezyang
ghstack dependencies: #107523
246 lines
6.8 KiB
Python
246 lines
6.8 KiB
Python
# Owner(s): ["module: dynamo"]
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import logging
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import unittest
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import torch
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import torch._dynamo
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import torch._dynamo.config
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import torch._dynamo.test_case
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from torch._dynamo.comptime import comptime
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from torch._dynamo.exc import Unsupported
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from torch.testing._internal.common_device_type import skipIf
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from torch.testing._internal.common_utils import munge_exc, TEST_Z3
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from torch.testing._internal.logging_utils import LoggingTestCase, make_logging_test
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class ExcTests(LoggingTestCase):
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maxDiff = None
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def test_unsupported_real_stack(self):
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# exercise Unsupported constructor and augment_exc_message
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def fn002(x):
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torch._dynamo.graph_break()
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def fn001(x):
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x = x + 1
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fn002(x)
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self.assertExpectedInlineMunged(
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Unsupported,
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lambda: torch.compile(fn001, backend="eager", fullgraph=True)(
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torch.randn(1)
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),
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"""\
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call_function graph_break in skip_files _dynamo/decorators.py
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from user code:
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File "test_exc.py", line N, in fn001
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fn002(x)
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File "test_exc.py", line N, in fn002
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torch._dynamo.graph_break()""",
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)
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@torch._dynamo.config.patch(verbose=True, suppress_errors=True)
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@make_logging_test()
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def test_internal_error_suppress_errors(self, records):
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def fn001(x):
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def f(ctx):
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raise AssertionError()
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comptime(f)
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torch.compile(fn001, backend="eager")(torch.randn(1))
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record = self.getRecord(records, "WON'T CONVERT")
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self.assertExpectedInline(
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munge_exc(record.getMessage()),
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"""\
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WON'T CONVERT fn001 test_exc.py line N
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========== TorchDynamo Stack Trace ==========
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Traceback (most recent call last):
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File "test_exc.py", line N, in f
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raise AssertionError()
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AssertionError:
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from user code:
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File "test_exc.py", line N, in fn001
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comptime(f)
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========== The above exception occurred while processing the following code ==========
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File "test_exc.py", line N, in test_internal_error_suppress_errors
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torch.compile(fn001, backend="eager")(torch.randn(1))
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File "test_exc.py", line N, in fn001
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comptime(f)
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==========""",
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)
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@make_logging_test()
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def test_not_implemented_error(self, records):
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def fn001(x):
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def f(ctx):
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raise NotImplementedError()
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# Ensure graph break is not possible
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for i in range(3):
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comptime(f)
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torch.compile(fn001, backend="eager")(torch.randn(1))
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record = self.getRecord(records, "WON'T CONVERT")
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self.assertExpectedInline(
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munge_exc(record.getMessage()),
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"""\
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WON'T CONVERT fn001 test_exc.py line N
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due to:
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Traceback (most recent call last):
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File "test_exc.py", line N, in f
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raise NotImplementedError()
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torch._dynamo.exc.InternalTorchDynamoError:
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from user code:
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File "test_exc.py", line N, in fn001
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comptime(f)""",
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)
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@unittest.expectedFailure
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@torch._dynamo.config.patch(inject_BUILD_SET_unimplemented_TESTING_ONLY=True)
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@make_logging_test(dynamo=logging.DEBUG)
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def test_unsupported_error(self, records):
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def fn001(x):
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return {1, 2}
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torch.compile(fn001, backend="eager")(torch.randn(1))
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# TODO: There is no graph break log! This is because the graph break
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# logging is not in a centralized location; unsupported
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# instruction bypasses it
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self.getRecord(records, "Graph break:")
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@torch._dynamo.config.patch(suppress_errors=False)
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def test_internal_error_no_suppress(self):
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def fn001(x):
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# NB: avoid decorator, as 3.11 changed the line number attributed
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# in this situation
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def f(ctx):
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raise AssertionError()
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comptime(f)
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# NB: OK for user code to be truncated here, because the regular
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# exception backtrace has the rest of the crumbs
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self.assertExpectedInlineMunged(
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AssertionError,
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lambda: torch.compile(fn001, backend="eager")(torch.randn(1)),
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"""\
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from user code:
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File "test_exc.py", line N, in fn001
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comptime(f)""",
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)
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@make_logging_test(graph_breaks=True)
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def test_graph_break_log(self, records):
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def fn002(x):
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x = x + 1
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torch._dynamo.graph_break()
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x = x + 1
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return x
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def fn001(x):
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return fn002(x)
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torch.compile(fn001, backend="eager")(torch.randn(1))
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record = self.getRecord(records, "Graph break:")
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# TODO: This should also report the enclosing frames; need to plumb
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# frame object to it
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self.assertExpectedInline(
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munge_exc(record.getMessage()),
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"""\
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Graph break: call_function graph_break in skip_files _dynamo/decorators.py from user code at:
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File "test_exc.py", line N, in fn001
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return fn002(x)
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File "test_exc.py", line N, in fn002
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torch._dynamo.graph_break()
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""",
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)
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@torch._dynamo.config.patch(suppress_errors=False)
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def test_backend_suppress_line(self):
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def fn001(x):
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x = torch.relu(x)
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return x + 1
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# Do NOT let this get attributed to x + 1
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self.assertExpectedInlineMunged(
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torch._dynamo.exc.BackendCompilerFailed,
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lambda: torch.compile(fn001, backend="relu_compile_error_TESTING_ONLY")(
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torch.randn(1)
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),
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"""\
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backend='relu_compile_error_TESTING_ONLY' raised:
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ReluCompileError:""",
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)
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@skipIf(not TEST_Z3, "z3 not installed")
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@torch._dynamo.config.patch(
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inject_EVALUATE_EXPR_flip_equality_TESTING_ONLY=True,
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assume_static_by_default=False,
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translation_validation=True,
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suppress_errors=False,
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)
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def test_trigger_on_error(self):
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from torch.fx.experimental.validator import ValidationException
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@torch.compile
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def fn(x):
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return x.reshape(-1, 4)
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self.assertExpectedInlineMunged(
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ValidationException,
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lambda: fn(torch.randn(20)),
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"""\
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translation validation failed.
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Model:
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==> L['x'].storage_offset(): 0
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==> s0: 4
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==> L['x'].stride()[0]: 1
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==> L['x'].size()[0]: 4
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Assertions:
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==> (== L['x'].size()[0] s0)
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==> (> s0 1)
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==> (Not (And (< L['x'].size()[0] 4) (>= L['x'].size()[0] 0)))
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==> (True)
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==> (== 0 L['x'].storage_offset())
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==> (== 1 L['x'].stride()[0])
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==> (True)
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Target Expressions:
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==> (>= 9223372036854775806 s0)
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==> (== 4 L['x'].size()[0])
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==> (== 0 L['x'].storage_offset())
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==> (> s0 0)
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==> (== 1 L['x'].stride()[0])
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==> (<= 2 s0)
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==> (== 4 s0)
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Failed Source Expressions:
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==> (!= 4 L['x'].size()[0])""",
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)
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if __name__ == "__main__":
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from torch._dynamo.test_case import run_tests
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run_tests()
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