# Owner(s): ["module: dynamo"]

import logging
import unittest

import torch
import torch._dynamo
import torch._dynamo.config
import torch._dynamo.test_case
from torch._dynamo.comptime import comptime
from torch._dynamo.exc import Unsupported
from torch.testing._internal.common_device_type import skipIf
from torch.testing._internal.common_utils import munge_exc, TEST_Z3
from torch.testing._internal.logging_utils import LoggingTestCase, make_logging_test


class ExcTests(LoggingTestCase):
    maxDiff = None

    def test_unsupported_real_stack(self):
        # exercise Unsupported constructor and augment_exc_message
        def fn002(x):
            torch._dynamo.graph_break()

        def fn001(x):
            x = x + 1
            fn002(x)

        self.assertExpectedInlineMunged(
            Unsupported,
            lambda: torch.compile(fn001, backend="eager", fullgraph=True)(
                torch.randn(1)
            ),
            """\
'call_function graph_break in skip_files _dynamo/decorators.py, skipped according skipfiles.SKIP_DIRS'

from user code:
   File "test_exc.py", line N, in fn001
    fn002(x)
  File "test_exc.py", line N, in fn002
    torch._dynamo.graph_break()""",
        )

    @torch._dynamo.config.patch(verbose=True, suppress_errors=True)
    @make_logging_test()
    def test_internal_error_suppress_errors(self, records):
        def fn001(x):
            def f(ctx):
                raise AssertionError()

            comptime(f)

        torch.compile(fn001, backend="eager")(torch.randn(1))

        record = self.getRecord(records, "WON'T CONVERT")

        self.assertExpectedInline(
            munge_exc(record.getMessage()),
            """\
WON'T CONVERT fn001 test_exc.py line N
========== TorchDynamo Stack Trace ==========
Traceback (most recent call last):
  File "test_exc.py", line N, in f
    raise AssertionError()
AssertionError:

from user code:
   File "test_exc.py", line N, in fn001
    comptime(f)


========== The above exception occurred while processing the following code ==========

  File "test_exc.py", line N, in test_internal_error_suppress_errors
    torch.compile(fn001, backend="eager")(torch.randn(1))
  File "test_exc.py", line N, in fn001
    comptime(f)

==========""",
        )

    @make_logging_test()
    def test_not_implemented_error(self, records):
        def fn001(x):
            def f(ctx):
                raise NotImplementedError()

            # Ensure graph break is not possible
            for i in range(3):
                comptime(f)

        torch.compile(fn001, backend="eager")(torch.randn(1))

        record = self.getRecord(records, "WON'T CONVERT")

        self.assertExpectedInline(
            munge_exc(record.getMessage()),
            """\
WON'T CONVERT fn001 test_exc.py line N
due to:
Traceback (most recent call last):
  File "test_exc.py", line N, in f
    raise NotImplementedError()
torch._dynamo.exc.InternalTorchDynamoError:

from user code:
   File "test_exc.py", line N, in fn001
    comptime(f)""",
        )

    @unittest.expectedFailure
    @torch._dynamo.config.patch(inject_BUILD_SET_unimplemented_TESTING_ONLY=True)
    @make_logging_test(dynamo=logging.DEBUG)
    def test_unsupported_error(self, records):
        def fn001(x):
            return {1, 2}

        torch.compile(fn001, backend="eager")(torch.randn(1))

        # TODO: There is no graph break log!  This is because the graph break
        # logging is not in a centralized location; unsupported
        # instruction bypasses it
        self.getRecord(records, "Graph break:")

    @torch._dynamo.config.patch(suppress_errors=False)
    def test_internal_error_no_suppress(self):
        def fn001(x):
            # NB: avoid decorator, as 3.11 changed the line number attributed
            # in this situation
            def f(ctx):
                raise AssertionError()

            comptime(f)

        # NB: OK for user code to be truncated here, because the regular
        # exception backtrace has the rest of the crumbs
        self.assertExpectedInlineMunged(
            AssertionError,
            lambda: torch.compile(fn001, backend="eager")(torch.randn(1)),
            """\


from user code:
   File "test_exc.py", line N, in fn001
    comptime(f)""",
        )

    @make_logging_test(graph_breaks=True)
    def test_graph_break_log(self, records):
        def fn002(x):
            x = x + 1
            torch._dynamo.graph_break()
            x = x + 1
            return x

        def fn001(x):
            return fn002(x)

        torch.compile(fn001, backend="eager")(torch.randn(1))

        record = self.getRecord(records, "Graph break:")

        # TODO: This should also report the enclosing frames; need to plumb
        # frame object to it
        self.assertExpectedInline(
            munge_exc(record.getMessage()),
            """\
Graph break: 'call_function graph_break in skip_files _dynamo/decorators.py, skipped according skipfiles.SKIP_DIRS' from user code at:
  File "test_exc.py", line N, in fn001
    return fn002(x)
  File "test_exc.py", line N, in fn002
    torch._dynamo.graph_break()
""",  # noqa: B950
        )

    @torch._dynamo.config.patch(suppress_errors=False)
    def test_backend_suppress_line(self):
        def fn001(x):
            x = torch.relu(x)
            return x + 1

        # Do NOT let this get attributed to x + 1
        self.assertExpectedInlineMunged(
            torch._dynamo.exc.BackendCompilerFailed,
            lambda: torch.compile(fn001, backend="relu_compile_error_TESTING_ONLY")(
                torch.randn(1)
            ),
            """\
backend='relu_compile_error_TESTING_ONLY' raised:
ReluCompileError:""",
        )

    @skipIf(not TEST_Z3, "z3 not installed")
    @torch._dynamo.config.patch(
        inject_EVALUATE_EXPR_flip_equality_TESTING_ONLY=True,
        assume_static_by_default=False,
        translation_validation=True,
        translation_validation_no_bisect=True,
        suppress_errors=False,
    )
    def test_trigger_on_error(self):
        from torch.fx.experimental.validator import ValidationException

        @torch.compile
        def fn(x, shape):
            return x.split(shape)

        self.assertExpectedInlineMunged(
            ValidationException,
            lambda: fn(torch.randn(20), (5, 10, 5)),
            """\
translation validation failed.

Model:
  ==> L['shape'][0]: 0
  ==> L['shape'][1]: 0
  ==> L['shape'][2]: 0
  ==> L['x'].size()[0]: 3
  ==> L['x'].storage_offset(): 0
  ==> L['x'].stride()[0]: 1
  ==> s0: 3
  ==> s1: 0
  ==> s2: 0
  ==> s3: 0

Assertions:
  ==> (== 0 L['x'].storage_offset())
  ==> (== 1 L['x'].stride()[0])
  ==> (== L['shape'][0] s1)
  ==> (== L['shape'][1] s2)
  ==> (== L['shape'][2] s3)
  ==> (== L['x'].size()[0] s0)
  ==> (> s0 1)
  ==> (True)

Target Expressions:
  ==> (<= 0 s1)
  ==> (<= 0 s2)
  ==> (<= 0 s3)
  ==> (<= 2 s0)
  ==> (== 0 L['shape'][0])
  ==> (== 0 L['shape'][1])
  ==> (== 0 L['shape'][2])
  ==> (== 0 L['x'].storage_offset())
  ==> (== 0 s1)
  ==> (== 0 s2)
  ==> (== 0 s3)
  ==> (== 1 L['x'].stride()[0])
  ==> (== L['x'].size()[0] s0)
  ==> (> s0 0)
  ==> (>= 9223372036854775806 s0)
  ==> (>= 9223372036854775806 s1)
  ==> (>= 9223372036854775806 s2)
  ==> (>= 9223372036854775806 s3)

Failed Source Expressions:
  ==> (!= 0 L['shape'][0])
  ==> (!= 0 L['shape'][1])
  ==> (!= 0 L['shape'][2])
  ==> (== (+ L['shape'][0] L['shape'][1] L['shape'][2]) L['x'].size()[0])""",
        )

    @skipIf(not TEST_Z3, "z3 not installed")
    @torch._dynamo.config.patch(
        inject_EVALUATE_EXPR_flip_equality_TESTING_ONLY=True,
        assume_static_by_default=False,
        translation_validation=True,
        suppress_errors=False,
    )
    def test_trigger_bisect_on_error(self):
        from torch.fx.experimental.validator import BisectValidationException

        @torch.compile
        def fn(x, shape):
            return x.split(shape)

        self.assertExpectedInlineMunged(
            BisectValidationException,
            lambda: fn(torch.randn(20), (5, 10, 5)),
            """\
translation validation failed when evaluating: Eq(s1 + s2 + s3, s0)

Failure ocurred while running node:
    %split : [num_users=1] = call_method[target=split](args = (%l_x_, (%l_shape_0_, %l_shape_1_, %l_shape_2_)), kwargs = {})

Model:
  ==> L['shape'][0]: -9223372036854775807
  ==> L['shape'][1]: -9223372036854775807
  ==> L['shape'][2]: -9223372036854775807
  ==> L['x'].size()[0]: 3
  ==> L['x'].storage_offset(): 0
  ==> L['x'].stride()[0]: 1
  ==> s0: 3
  ==> s1: -9223372036854775807
  ==> s2: -9223372036854775807
  ==> s3: -9223372036854775807

Assertions:
  ==> (== 0 L['x'].storage_offset())
  ==> (== 1 L['x'].stride()[0])
  ==> (== L['shape'][0] s1)
  ==> (== L['shape'][1] s2)
  ==> (== L['shape'][2] s3)
  ==> (== L['x'].size()[0] s0)
  ==> (> s0 1)

Target Expressions:
  ==> (!= (+ s1 s2 s3) s0)
  ==> (<= -9223372036854775808 s1)
  ==> (<= -9223372036854775808 s2)
  ==> (<= -9223372036854775808 s3)
  ==> (<= 2 s0)
  ==> (== 0 L['x'].storage_offset())
  ==> (== 1 L['x'].stride()[0])
  ==> (== L['shape'][0] s1)
  ==> (== L['shape'][1] s2)
  ==> (== L['shape'][2] s3)
  ==> (== L['x'].size()[0] s0)
  ==> (> s0 0)
  ==> (>= 9223372036854775806 s0)
  ==> (>= 9223372036854775807 s1)
  ==> (>= 9223372036854775807 s2)
  ==> (>= 9223372036854775807 s3)

Failed Source Expressions:
  ==> (== (+ L['shape'][0] L['shape'][1] L['shape'][2]) L['x'].size()[0])""",
        )


if __name__ == "__main__":
    from torch._dynamo.test_case import run_tests

    run_tests()