skipIfTorchInductor Tracking Issue 
Labels: good first issue, triaged, oncall: pt2, module: inductor

### 🐛 Describe the bug

We have a long list of known failures in test_torch.py.

./test/test_torch.py:
- [x] 'test_scalar_check' - "segfaults"
- [x] 'test_conv_transposed_backward_agnostic_to_memory_format' - "Please convert all Tensors to FakeTensors"
- [ ] 'test_sync_warning' - "FIXME"
- [x] 'test_copy_transpose_math_view' - https://github.com/pytorch/pytorch/issues/110291
- [x] 'test_errors_index_copy' - "FIXME"
- [x] 'test_scatter_reduce_non_unique_index' - "FIXME"
- [x] 'test_dim_function_empty' - "RuntimeError: Trying to create tensor with negative dimension -1: [-1]" - https://github.com/pytorch/pytorch/pull/106994
- [x] 'test_ternary_op_mem_overlap' - "FIXME"
- [x] 'test_multinomial_device_constrain' - "out_wrapper does not check devices correctly"
- [x] 'test_multinomial_gpu_device_constrain' - "out_wrapper does not check devices correctly"
- [x] 'test_memory_format_propagation_rules' - "To be supported"
- [x] 'test_memory_format_empty_like' - "To be supported"
- [x] 'test_memory_format_operators' - "To be supported"
- [x] 'test_pin_memory_from_constructor' - "pin_memory isn't yet supported in TorchInductor"
- [x] 'test_memory_format_to' - "To be supported"
- [x] 'test_memory_format_type' - "To be supported"
- [x] 'test_memory_format_clone' - "To be supported"
- [x] 'test_memory_format_factory_like_functions_preserve' - "To be supported" (@masnesral)
- [x] 'test_memory_format_type_shortcuts' - "To be supported"
- [x] 'test_memory_format_cpu_and_cuda_ops' - "To be supported"
- [ ] 'test_hook_remove' - "FIXME"
- [x] 'test_assertRaisesRegex_ignore_msg_non_native_device' - "random_.from needs to be renamed"
- [x] 'test_advancedindex_mixed_cpu_devices' - "FIXME"
- [x] 'test_advancedindex_mixed_devices_error' - "FIXME"
- [ ] #108181 and https://github.com/pytorch/pytorch/issues/108798
- [ ] 'test_typed_storage_deprecation_warning' - "FIXME"
- [x] 'test_pin_memory' - "pin_memory isn't yet supported in TorchInductor"
- [x] 'test_memory_format' - "To be supported"
- [x] 'test_upsample_nearest2d_meta' - "https://github.com/pytorch/pytorch/issues/97414"
- [x] 'test_copy_broadcast' - "FIXME"
- [x] 'test_copy_many_to_one' - https://github.com/pytorch/pytorch/pull/108989
- [x] 'test_copy_float16' - "FIXME"
- [x] 'test_to' - "FIXME"
- [x] 'test_slice' - "FIXME"


All the non deterministic tests are low pri, but it might be easy enough to fix
- [ ] (one issue)
'test_nondeterministic_alert_AvgPool3d' - "aot-autograd issue"
'test_nondeterministic_alert_AdaptiveAvgPool2d' - "aot-autograd issue"
'test_nondeterministic_alert_AdaptiveAvgPool3d' - "aot-autograd issue"
'test_nondeterministic_alert_MaxPool3d' - "aot-autograd issue"
'test_nondeterministic_alert_AdaptiveMaxPool2d' - "aot-autograd issue"
'test_nondeterministic_alert_FractionalMaxPool2d' - "aot-autograd issue"
'test_nondeterministic_alert_FractionalMaxPool3d' - "aot-autograd issue"
'test_nondeterministic_alert_interpolate_linear' - "aot-autograd issue"
'test_nondeterministic_alert_interpolate_bilinear' - "aot-autograd issue"
'test_deterministic_interpolate_bilinear' - "aot-autograd issue"
'test_nondeterministic_alert_interpolate_bicubic' - "aot-autograd issue"
'test_nondeterministic_alert_interpolate_trilinear' - "aot-autograd issue"
'test_nondeterministic_alert_ReflectionPad1d' - "aot-autograd issue"
'test_nondeterministic_alert_ReflectionPad2d' - "aot-autograd issue"
'test_nondeterministic_alert_ReflectionPad3d' - "aot-autograd issue"
'test_nondeterministic_alert_ReplicationPad1d' - "aot-autograd issue"
'test_nondeterministic_alert_ReplicationPad2d' - "aot-autograd issue"
'test_nondeterministic_alert_ReplicationPad3d' - "aot-autograd issue"
'test_nondeterministic_alert_CTCLoss' - "aot-autograd issue"
'test_nondeterministic_alert_EmbeddingBag_max' - "aot-autograd issue"
'test_nondeterministic_alert_cumsum' - "aot-autograd issue"
'test_nondeterministic_alert_put_accumulate' - "warning is logged from the FallbackKernel: torch.ops.aten.put_.default when warn_only=True"
'test_nondeterministic_alert_grid_sample_2d' - "aot-autograd issue"
'test_nondeterministic_alert_grid_sample_3d' - "aot-autograd issue"

./test/test_modules.py:
- [x] 'test_cpu_gpu_parity' - "to be fixed"
- [x] 'test_memory_format' - "to be fixed"
- [x] 'test_non_contiguous_tensors - "to be fixed"

These are lower priority than 

./test/test_ops.py
- [x] 'test_out_warning' - "rng mismatch"
- [x] 'test_out' - "rng mismatch"
- [x] 'test_variant_consistency_eager' - "complex error"
- [x] 'test_complex_half_reference_testing' - "complex error"
- [x] 'test_non_standard_bool_values' - "Inductor does not support view with dtype yet"

Following root cause is https://github.com/pytorch/pytorch/issues/107861#issuecomment-1708955469
- [x] 'test_conj_view' - "complex error" (fails with aot_eager) (@int3)
- [x] 'test_neg_view' - "grad error " (fails with aot_eager)
- [x] 'test_neg_conj_view' - "grad error" (fails with aot_eager



Test that take too long (defer for now, eventually find way to run periodically)

Covered by torchinductor opinfo tests
- [x] 'test_python_ref_meta' - "Takes too long for inductor" (skip or find way to run periodically)
- [x] 'test_python_ref' - "Takes too long for inductor" (skip or find way to run periodically)
- [x] 'test_python_ref_torch_fallback' - "Takes too long for inductor" (skip or find way to run periodically)
- [x] 'test_python_ref_executor' - "Takes too long for inductor" (skip or find way to run periodically)
- [x] 'test_python_ref_errors' - "Takes too long for inductor" (skip or find way to run periodically)

./test/test_ops_fwd_gradients.py:
- [ ] 'test_inplace_forward_mode_AD' - "to be fixed" (lower pri)

### Versions

master

cc @ezyang @msaroufim @wconstab @bdhirsh @anijain2305 @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @Xia-Weiwen @wenzhe-nrv @jiayisunx @peterbell10 @ipiszy @ngimel @yf225 @chenyang78