Fix exception chaining in torch/ (#43836)

Summary:
## Motivation
Fixes https://github.com/pytorch/pytorch/issues/43770.

## Description of the change
This PR fixes exception chaining only in files under `torch/` where appropriate.
To fix exception chaining, I used either:
1. `raise new_exception from old_exception` where `new_exception` itself seems not descriptive enough to debug or `old_exception` delivers valuable information.
2. `raise new_exception from None` where raising both of `new_exception` and `old_exception` seems a bit noisy and redundant.
I subjectively chose which one to use from the above options.

## List of lines containing raise in except clause:
I wrote [this simple script](https://gist.github.com/akihironitta/4223c1b32404b36c1b349d70c4c93b4d) using [ast](https://docs.python.org/3.8/library/ast.html#module-ast) to list lines where `raise`ing in `except` clause.

- [x] 000739c31a/torch/jit/annotations.py (L35)
- [x] 000739c31a/torch/jit/annotations.py (L150)
- [x] 000739c31a/torch/jit/annotations.py (L158)
- [x] 000739c31a/torch/jit/annotations.py (L231)
- [x] 000739c31a/torch/jit/_trace.py (L432)
- [x] 000739c31a/torch/nn/utils/prune.py (L192)
- [x] 000739c31a/torch/cuda/nvtx.py (L7)
- [x] 000739c31a/torch/utils/cpp_extension.py (L1537)
- [x] 000739c31a/torch/utils/tensorboard/_pytorch_graph.py (L292)
- [x] 000739c31a/torch/utils/data/dataloader.py (L835)
- [x] 000739c31a/torch/utils/data/dataloader.py (L849)
- [x] 000739c31a/torch/utils/data/dataloader.py (L856)
- [x] 000739c31a/torch/testing/_internal/common_utils.py (L186)
- [x] 000739c31a/torch/testing/_internal/common_utils.py (L189)
- [x] 000739c31a/torch/testing/_internal/common_utils.py (L424)
- [x] 000739c31a/torch/testing/_internal/common_utils.py (L1279)
- [x] 000739c31a/torch/testing/_internal/common_utils.py (L1283)
- [x] 000739c31a/torch/testing/_internal/common_utils.py (L1356)
- [x] 000739c31a/torch/testing/_internal/common_utils.py (L1388)
- [x] 000739c31a/torch/testing/_internal/common_utils.py (L1391)
- [ ] 000739c31a/torch/testing/_internal/common_utils.py (L1412)
- [x] 000739c31a/torch/testing/_internal/codegen/random_topo_test.py (L310)
- [x] 000739c31a/torch/testing/_internal/codegen/random_topo_test.py (L329)
- [x] 000739c31a/torch/testing/_internal/codegen/random_topo_test.py (L332)
- [x] 000739c31a/torch/testing/_internal/jit_utils.py (L183)
- [x] 000739c31a/torch/testing/_internal/common_nn.py (L4789)
- [x] 000739c31a/torch/onnx/utils.py (L367)
- [x] 000739c31a/torch/onnx/utils.py (L659)
- [x] 000739c31a/torch/onnx/utils.py (L892)
- [x] 000739c31a/torch/onnx/utils.py (L897)
- [x] 000739c31a/torch/serialization.py (L108)
- [x] 000739c31a/torch/serialization.py (L754)
- [x] 000739c31a/torch/distributed/rpc/_testing/faulty_agent_backend_registry.py (L76)
- [x] 000739c31a/torch/distributed/rpc/backend_registry.py (L260)
- [x] 000739c31a/torch/distributed/distributed_c10d.py (L184)
- [x] 000739c31a/torch/_utils_internal.py (L57)
- [x] 000739c31a/torch/hub.py (L494)
- [x] 000739c31a/torch/contrib/_tensorboard_vis.py (L16)
- [x] 000739c31a/torch/distributions/lowrank_multivariate_normal.py (L100)
- [x] 000739c31a/torch/distributions/constraint_registry.py (L142)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/43836

Reviewed By: ailzhang

Differential Revision: D23431212

Pulled By: malfet

fbshipit-source-id: 5f7f41b391164a5ad0efc06e55cd58c23408a921

torch/_utils_internal.py

@@ -49,12 +49,12 @@ def get_source_lines_and_file(obj, error_msg=None):
         filename = inspect.getsourcefile(obj)
         sourcelines, file_lineno = inspect.getsourcelines(obj)
     except OSError as e:
-        msg = ("Can't get source for {}. TorchScript requires source access in "
+        msg = (f"Can't get source for {obj}. TorchScript requires source access in "
                "order to carry out compilation, make sure original .py files are "
-               "available. Original error: {}".format(obj, e))
+               "available.")
         if error_msg:
             msg += '\n' + error_msg
-        raise OSError(msg)
+        raise OSError(msg) from e
 
     return sourcelines, file_lineno, filename
 

torch/contrib/_tensorboard_vis.py

@@ -14,7 +14,7 @@ try:
     from tensorflow.python.summary.writer.writer import FileWriter
 except ImportError:
     raise ImportError("TensorBoard visualization of GraphExecutors requires having "
-                      "TensorFlow installed")
+                      "TensorFlow installed") from None
 
 
 def dump_tensorboard_summary(graph_executor, logdir):

torch/distributed/distributed_c10d.py

@@ -181,7 +181,7 @@ def _get_group_rank(group, rank):
     try:
         group_rank = _pg_group_ranks[group][rank]
     except KeyError:
-        raise RuntimeError("The global rank is not part of the group")
+        raise RuntimeError(f"The global rank {rank} is not part of the group {group}") from None
     return group_rank
 
 

torch/distributions/constraint_registry.py

@@ -140,7 +140,7 @@ class ConstraintRegistry(object):
             factory = self._registry[type(constraint)]
         except KeyError:
             raise NotImplementedError(
-                'Cannot transform {} constraints'.format(type(constraint).__name__))
+                f'Cannot transform {type(constraint).__name__} constraints') from None
         return factory(constraint)
 
 

torch/distributions/lowrank_multivariate_normal.py

@@ -96,9 +96,9 @@ class LowRankMultivariateNormal(Distribution):
         cov_diag_ = cov_diag.unsqueeze(-1)
         try:
             loc_, self.cov_factor, cov_diag_ = torch.broadcast_tensors(loc_, cov_factor, cov_diag_)
-        except RuntimeError:
+        except RuntimeError as e:
             raise ValueError("Incompatible batch shapes: loc {}, cov_factor {}, cov_diag {}"
-                             .format(loc.shape, cov_factor.shape, cov_diag.shape))
+                             .format(loc.shape, cov_factor.shape, cov_diag.shape)) from e
         self.loc = loc_[..., 0]
         self.cov_diag = cov_diag_[..., 0]
         batch_shape = self.loc.shape[:-1]

torch/jit/_trace.py

@@ -433,9 +433,8 @@ def _check_trace(
                     *graph_diagnostic_info(),
                     extra_msg="Encountered an exception while running the "
                     + running_what
-                    + " with test inputs.\nException:\n"
-                    + indent(str(e))
-                )
+                    + " with test inputs."
+                ) from e
 
         has_warned = [False]
 

torch/jit/annotations.py

@@ -32,7 +32,7 @@ class Module(object):
         try:
             return self.members[name]
         except KeyError:
-            raise RuntimeError("Module {} has no member called {}".format(self.name, name))
+            raise RuntimeError("Module {} has no member called {}".format(self.name, name)) from None
 
 
 class EvalEnv(object):
@@ -147,7 +147,7 @@ def parse_type_line(type_line, rcb, loc):
     try:
         arg_ann = eval(arg_ann_str, {}, EvalEnv(rcb))  # noqa: P204
     except (NameError, SyntaxError) as e:
-        raise RuntimeError("Failed to parse the argument list of a type annotation: {}".format(str(e)))
+        raise RuntimeError("Failed to parse the argument list of a type annotation") from e
 
     if not isinstance(arg_ann, tuple):
         arg_ann = (arg_ann,)
@@ -155,7 +155,7 @@ def parse_type_line(type_line, rcb, loc):
     try:
         ret_ann = eval(ret_ann_str, {}, EvalEnv(rcb))  # noqa: P204
     except (NameError, SyntaxError) as e:
-        raise RuntimeError("Failed to parse the return type of a type annotation: {}".format(str(e)))
+        raise RuntimeError("Failed to parse the return type of a type annotation") from e
 
     arg_types = [ann_to_type(ann, loc) for ann in arg_ann]
     return arg_types, ann_to_type(ret_ann, loc)
@@ -228,7 +228,7 @@ def split_type_line(type_line):
     try:
         arrow_pos = type_line.index('->')
     except ValueError:
-        raise RuntimeError("Syntax error in type annotation (cound't find `->`)")
+        raise RuntimeError("Syntax error in type annotation (cound't find `->`)") from None
     return type_line[start_offset:arrow_pos].strip(), type_line[arrow_pos + 2:].strip()
 
 

torch/onnx/utils.py

@@ -363,8 +363,8 @@ def _model_to_graph(model, args, verbose=False,
             in_vars, in_desc = torch.jit._flatten(tuple(args) + tuple(params))
             graph = _propagate_and_assign_input_shapes(
                 method_graph, tuple(in_vars), False, propagate)
-        except AttributeError:
-            raise RuntimeError('\'forward\' method must be a script method')
+        except AttributeError as e:
+            raise RuntimeError('\'forward\' method must be a script method') from e
     elif isinstance(model, torch.jit.ScriptFunction):
         assert example_outputs is not None, "example_outputs must be provided when exporting a TorchScript ScriptFunction"
         method = model

torch/serialization.py

@@ -105,7 +105,7 @@ def check_module_version_greater_or_equal(module, req_version_tuple, error_if_ma
             module.__name__, module.__version__, str(req_version_tuple)
         )
         if error_if_malformed:
-            raise RuntimeError(message)
+            raise RuntimeError(message) from e
         else:
             warnings.warn(message + ', but continuing assuming that requirement is met')
             requirement_is_met = True
@@ -752,7 +752,7 @@ def _legacy_load(f, map_location, pickle_module, **pickle_load_args):
             if _is_zipfile(f):
                 # .zip is used for torch.jit.save and will throw an un-pickling error here
                 raise RuntimeError(
-                    "{filename} is a zip archive (did you mean to use torch.jit.load()?)".format(filename=f.name))
+                    f"{f.name} is a zip archive (did you mean to use torch.jit.load()?)") from None
             # if not a tarfile, reset file offset and proceed
             f.seek(0)
 

torch/testing/_internal/codegen/random_topo_test.py

@@ -307,8 +307,8 @@ def runTest(seed, args):
             for out in o:
                 print("val size: ", out.size())
     except Exception as err:
-        raise Exception("Testing script failure with error message {0}\n\trepro by running:\n\t{1}".format(
-            str(err), reproString(seed, args)))
+        raise Exception("Testing script failure with error message, repro by running:\n"
+                        f"\t{reproString(seed, args)}") from err
     try:
         traced_model = torch.jit.trace(random_topology_test, (seed_tensor, *tensor_list))
         if DEBUG_PRINT:
@@ -325,12 +325,12 @@ def runTest(seed, args):
                 print("jit output: ", jit_oo)
                 print("diff ", jit_oo - oo)
                 raise WrongResultException()
-    except WrongResultException:
+    except WrongResultException as err:
         raise Exception("cuda fuser gives wrong results, repro by running:\n"
-                        "\t{0}".format(reproString(seed, args)))
+                        f"\t{reproString(seed, args)}") from err
     except Exception as err:
-        raise Exception("something in cuda fuser went wrong {0}\n\trepro by running:\n\t{1}".format(
-            str(err), reproString(seed, args)))
+        raise Exception("something in cuda fuser went wrong, repro by running:\n"
+                        f"\t{reproString(seed, args)}") from err
 
 
 def parse_args():

torch/testing/_internal/common_utils.py

@@ -1283,7 +1283,7 @@ class TestCase(expecttest.TestCase):
                 raise RuntimeError(
                     ("I got this output for {}{}:\n\n{}\n\n"
                      "No expect file exists; to accept the current output, run:\n"
-                     "python {} {} --accept").format(munged_id, subname_output, s, __main__.__file__, munged_id))
+                     "python {} {} --accept").format(munged_id, subname_output, s, __main__.__file__, munged_id)) from None
 
         # a hack for JIT tests
         if IS_WINDOWS:
@@ -1350,10 +1350,10 @@ def download_file(url, binary=True):
         with open(path, 'wb' if binary else 'w') as f:
             f.write(data)
         return path
-    except error.URLError:
+    except error.URLError as e:
         msg = "could not download test file '{}'".format(url)
         warnings.warn(msg, RuntimeWarning)
-        raise unittest.SkipTest(msg)
+        raise unittest.SkipTest(msg) from e
 
 
 def find_free_port():

torch/utils/cpp_extension.py

@@ -1525,7 +1525,7 @@ def _run_ninja_build(build_directory: str, verbose: bool, error_prefix: str) ->
                 stderr=subprocess.STDOUT,
                 cwd=build_directory,
                 env=env)
-    except subprocess.CalledProcessError:
+    except subprocess.CalledProcessError as e:
         # Python 2 and 3 compatible way of getting the error object.
         _, error, _ = sys.exc_info()
         # error.output contains the stdout and stderr of the build attempt.
@@ -1534,7 +1534,7 @@ def _run_ninja_build(build_directory: str, verbose: bool, error_prefix: str) ->
         # mypy thinks it's Optional[BaseException] and doesn't narrow
         if hasattr(error, 'output') and error.output:  # type: ignore
             message += ": {}".format(error.output.decode())  # type: ignore
-        raise RuntimeError(message)
+        raise RuntimeError(message) from e
 
 
 def _import_module_from_library(module_name, path, is_python_module):

torch/utils/data/dataloader.py

@@ -832,7 +832,7 @@ class _MultiProcessingDataLoaderIter(_BaseDataLoaderIter):
                     self._shutdown_worker(worker_id)
             if len(failed_workers) > 0:
                 pids_str = ', '.join(str(w.pid) for w in failed_workers)
-                raise RuntimeError('DataLoader worker (pid(s) {}) exited unexpectedly'.format(pids_str))
+                raise RuntimeError('DataLoader worker (pid(s) {}) exited unexpectedly'.format(pids_str)) from e
             if isinstance(e, queue.Empty):
                 return (False, None)
             import tempfile
@@ -852,7 +852,7 @@ class _MultiProcessingDataLoaderIter(_BaseDataLoaderIter):
                         " limit using `ulimit -n` in the shell or change the"
                         " sharing strategy by calling"
                         " `torch.multiprocessing.set_sharing_strategy('file_system')`"
-                        " at the beginning of your code")
+                        " at the beginning of your code") from None
             raise
 
 # NOTE [ DataLoader on Linux and open files limit ]