[CI] Fix python file format due to changes in black

apps/extension/python/tvm_ext/__init__.py

@@ -44,7 +44,7 @@ def load_lib():
 
 @tvm.register_object("tvm_ext.IntVector")
 class IntVec(tvm.Object):
- """Example for using extension class in c++"""
+ """Example for using extension class in c++"""
 
  @property
  def _tvm_handle(self):

python/tvm/_ffi/_ctypes/packed_func.py

@@ -73,7 +73,7 @@ def convert_to_tvm_func(pyfunc):
  local_pyfunc = pyfunc
 
  def cfun(args, type_codes, num_args, ret, _):
- """ctypes function"""
+ """ctypes function"""
  num_args = num_args.value if isinstance(num_args, ctypes.c_int) else num_args
  pyargs = (C_TO_PY_ARG_SWITCH[type_codes[i]](args[i]) for i in range(num_args))
  # pylint: disable=broad-except

python/tvm/arith/analyzer.py

@@ -22,7 +22,7 @@
 
 @tvm._ffi.register_object("arith.ModularSet")
 class ModularSet(Object):
- """Represent range of (coeff * x + base) for x in Z"""
+ """Represent range of (coeff * x + base) for x in Z"""
 
  def __init__(self, coeff, base):
  self.__init_handle_by_constructor__(_ffi_api.ModularSet, coeff, base)

python/tvm/auto_scheduler/loop_state.py

@@ -48,12 +48,12 @@
 
 @tvm._ffi.register_object("auto_scheduler.Iterator")
 class Iterator(Object):
- """A loop iterator structure."""
+ """A loop iterator structure."""
 
 
 @tvm._ffi.register_object("auto_scheduler.Stage")
 class Stage(Object):
- """A stage in the compute declaration. Similar to tvm.te.schedule.Stage."""
+ """A stage in the compute declaration. Similar to tvm.te.schedule.Stage."""
 
  # Static trans table for compute_at location
  # This is used to transform the compute_at location to C++ enum
@@ -62,7 +62,7 @@ class Stage(Object):
 
 @tvm._ffi.register_object("auto_scheduler.State")
 class StateObject(Object):
- """The internal State object"""
+ """The internal State object"""
 
  def __eq__(self, other):
  return _ffi_api.StateEqual(self, other)
@@ -579,7 +579,7 @@ def rfactor(self, stage, iterator, factor_iter_id):
  return self.stages[int(new_stage_id)].op
 
  def copy(self):
- """Do deep copy of this State."""
+ """Do deep copy of this State."""
  state = State(self.state_object, self.compute_dag)
  state.stage_id_map = self.stage_id_map.copy()
  return state

python/tvm/auto_scheduler/measure.py

@@ -84,7 +84,7 @@ class BuildFunc:
 
 @tvm._ffi.register_object("auto_scheduler.MeasureCallback")
 class MeasureCallback(Object):
- """The base class of measurement callback functions."""
+ """The base class of measurement callback functions."""
 
 
 @tvm._ffi.register_object("auto_scheduler.PythonBasedMeasureCallback")
@@ -244,7 +244,7 @@ def recover_measure_input(inp, rebuild_state=False):
 
 @tvm._ffi.register_object("auto_scheduler.ProgramBuilder")
 class ProgramBuilder(Object):
- """The base class of ProgramBuilders."""
+ """The base class of ProgramBuilders."""
 
  def build(self, measure_inputs, verbose=1):
  """Build programs and return results.
@@ -265,7 +265,7 @@ def build(self, measure_inputs, verbose=1):
 
 @tvm._ffi.register_object("auto_scheduler.ProgramRunner")
 class ProgramRunner(Object):
- """The base class of ProgramRunners."""
+ """The base class of ProgramRunners."""
 
  def run(self, measure_inputs, build_results, verbose=1):
  """Run measurement and return results.
@@ -585,7 +585,7 @@ def __del__(self):
 
 
 class MeasureErrorNo(object):
- """Error type for MeasureResult."""
+ """Error type for MeasureResult."""
 
  NO_ERROR = 0 # No error
  INSTANTIATION_ERROR = 1 # Errors happen when apply transform steps from init state

python/tvm/auto_scheduler/search_policy.py

@@ -96,7 +96,7 @@ def __init__(self, meet_condition_func, apply_func, rule_name="CustomSketchRule"
 
 @tvm._ffi.register_object("auto_scheduler.SearchPolicy")
 class SearchPolicy(Object):
- """The base class of search policies."""
+ """The base class of search policies."""
 
  def continue_search_one_round(self, num_measure, measurer):
  """

python/tvm/auto_scheduler/task_scheduler.py

@@ -540,7 +540,7 @@ def _restore_status(self, log_file, num_measures_per_round):
 
 
 class TaskSchedulerCallback:
- """The base class of task scheduler callback functions."""
+ """The base class of task scheduler callback functions."""
 
  def pre_tune(self, task_scheduler, task_id):
  """The callback before tuning each task.

python/tvm/auto_scheduler/utils.py

@@ -190,7 +190,7 @@ def get_const_tuple(in_tuple):
 
 
 def list_to_tuple(x):
- """Convert a list to a tuple recursively."""
+ """Convert a list to a tuple recursively."""
  assert isinstance(x, list)
  return tuple(list_to_tuple(y) if isinstance(y, list) else y for y in x)
 
@@ -250,7 +250,7 @@ def kill_child_processes(parent_pid, sig=signal.SIGTERM):
 
 
 def make_traceback_info():
- """Get the error message from traceback."""
+ """Get the error message from traceback."""
  info = str(traceback.format_exc())
  if len(info) > MAX_TRACEBACK_INFO_LEN:
  info = (

python/tvm/contrib/cc.py

@@ -92,7 +92,7 @@ def get_target_by_dump_machine(compiler):
  """
 
  def get_target_triple():
- """Get target triple according to dumpmachine option of compiler."""
+ """Get target triple according to dumpmachine option of compiler."""
  if compiler:
  cmd = [compiler, "-dumpmachine"]
  proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)

python/tvm/contrib/peak.py

@@ -26,7 +26,7 @@
 
 
 def _convert_to_remote(func, remote):
- """convert module function to remote rpc function"""
+ """convert module function to remote rpc function"""
  temp = utils.tempdir()
  path_dso = temp.relpath("tmp_func.tar")
  func.export_library(path_dso)

python/tvm/contrib/tedd.py

@@ -147,7 +147,7 @@ def get_itervar_label_color(itervar, iv_type):
 
 
 def linebrk(s, n):
- """Break input string s with <br/> for every n charactors."""
+ """Break input string s with <br/> for every n charactors."""
  result = ""
  j = 0
  for i, c in enumerate(s):

python/tvm/driver/tvmc/autotuner.py

@@ -46,7 +46,7 @@
 
 @register_parser
 def add_tune_parser(subparsers):
- """Include parser for 'tune' subcommand"""
+ """Include parser for 'tune' subcommand"""
 
  parser = subparsers.add_parser("tune", help="auto-tune a model")
  parser.set_defaults(func=drive_tune)

python/tvm/driver/tvmc/frontends.py

@@ -77,7 +77,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 def import_keras():
- """Lazy import function for Keras"""
+ """Lazy import function for Keras"""
  # Keras writes the message "Using TensorFlow backend." to stderr
  # Redirect stderr during the import to disable this
  stderr = sys.stderr
@@ -93,7 +93,7 @@ def import_keras():
 
 
 class KerasFrontend(Frontend):
- """Keras frontend for TVMC"""
+ """Keras frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -151,7 +151,7 @@ def sequential_to_functional(self, model):
 
 
 class OnnxFrontend(Frontend):
- """ONNX frontend for TVMC"""
+ """ONNX frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -172,7 +172,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class TensorflowFrontend(Frontend):
- """TensorFlow frontend for TVMC"""
+ """TensorFlow frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -199,7 +199,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class TFLiteFrontend(Frontend):
- """TFLite frontend for TVMC"""
+ """TFLite frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -237,7 +237,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class PyTorchFrontend(Frontend):
- """PyTorch frontend for TVMC"""
+ """PyTorch frontend for TVMC"""
 
  @staticmethod
  def name():

python/tvm/driver/tvmc/main.py

@@ -53,7 +53,7 @@ def _example_parser(main_subparser):
 
 
 def _main(argv):
- """TVM command line interface."""
+ """TVM command line interface."""
 
  parser = argparse.ArgumentParser(
  prog="tvmc",

python/tvm/relay/analysis/feature.py

@@ -20,7 +20,7 @@
 
 
 class Feature(IntEnum):
- """The features a program might contain."""
+ """The features a program might contain."""
 
  fVar = 0
  fGlobalVar = 1

python/tvm/relay/backend/executor_factory.py

@@ -31,7 +31,7 @@ class ExecutorFactoryModule:
 
  @abstractmethod
  def get_executor_config(self):
- """Return the internal configuration the executor uses to execute the network"""
+ """Return the internal configuration the executor uses to execute the network"""
  raise NotImplementedError
 
  @abstractmethod
@@ -41,7 +41,7 @@ def get_params(self):
 
  @abstractmethod
  def get_lib(self):
- """Return the generated library"""
+ """Return the generated library"""
  raise NotImplementedError
 
  def __getitem__(self, item):

apps/extension/python/tvm_ext/__init__.py

@@ -44,7 +44,7 @@ def load_lib():
 
 @tvm.register_object("tvm_ext.IntVector")
 class IntVec(tvm.Object):
- """Example for using extension class in c++"""
+ """Example for using extension class in c++"""
 
  @property
  def _tvm_handle(self):

python/tvm/_ffi/_ctypes/packed_func.py

@@ -73,7 +73,7 @@ def convert_to_tvm_func(pyfunc):
  local_pyfunc = pyfunc
 
  def cfun(args, type_codes, num_args, ret, _):
- """ctypes function"""
+ """ctypes function"""
  num_args = num_args.value if isinstance(num_args, ctypes.c_int) else num_args
  pyargs = (C_TO_PY_ARG_SWITCH[type_codes[i]](args[i]) for i in range(num_args))
  # pylint: disable=broad-except

python/tvm/arith/analyzer.py

@@ -22,7 +22,7 @@
 
 @tvm._ffi.register_object("arith.ModularSet")
 class ModularSet(Object):
- """Represent range of (coeff * x + base) for x in Z"""
+ """Represent range of (coeff * x + base) for x in Z"""
 
  def __init__(self, coeff, base):
  self.__init_handle_by_constructor__(_ffi_api.ModularSet, coeff, base)

python/tvm/auto_scheduler/loop_state.py

@@ -48,12 +48,12 @@
 
 @tvm._ffi.register_object("auto_scheduler.Iterator")
 class Iterator(Object):
- """A loop iterator structure."""
+ """A loop iterator structure."""
 
 
 @tvm._ffi.register_object("auto_scheduler.Stage")
 class Stage(Object):
- """A stage in the compute declaration. Similar to tvm.te.schedule.Stage."""
+ """A stage in the compute declaration. Similar to tvm.te.schedule.Stage."""
 
  # Static trans table for compute_at location
  # This is used to transform the compute_at location to C++ enum
@@ -62,7 +62,7 @@ class Stage(Object):
 
 @tvm._ffi.register_object("auto_scheduler.State")
 class StateObject(Object):
- """The internal State object"""
+ """The internal State object"""
 
  def __eq__(self, other):
  return _ffi_api.StateEqual(self, other)
@@ -579,7 +579,7 @@ def rfactor(self, stage, iterator, factor_iter_id):
  return self.stages[int(new_stage_id)].op
 
  def copy(self):
- """Do deep copy of this State."""
+ """Do deep copy of this State."""
  state = State(self.state_object, self.compute_dag)
  state.stage_id_map = self.stage_id_map.copy()
  return state

python/tvm/auto_scheduler/measure.py

@@ -84,7 +84,7 @@ class BuildFunc:
 
 @tvm._ffi.register_object("auto_scheduler.MeasureCallback")
 class MeasureCallback(Object):
- """The base class of measurement callback functions."""
+ """The base class of measurement callback functions."""
 
 
 @tvm._ffi.register_object("auto_scheduler.PythonBasedMeasureCallback")
@@ -244,7 +244,7 @@ def recover_measure_input(inp, rebuild_state=False):
 
 @tvm._ffi.register_object("auto_scheduler.ProgramBuilder")
 class ProgramBuilder(Object):
- """The base class of ProgramBuilders."""
+ """The base class of ProgramBuilders."""
 
  def build(self, measure_inputs, verbose=1):
  """Build programs and return results.
@@ -265,7 +265,7 @@ def build(self, measure_inputs, verbose=1):
 
 @tvm._ffi.register_object("auto_scheduler.ProgramRunner")
 class ProgramRunner(Object):
- """The base class of ProgramRunners."""
+ """The base class of ProgramRunners."""
 
  def run(self, measure_inputs, build_results, verbose=1):
  """Run measurement and return results.
@@ -585,7 +585,7 @@ def __del__(self):
 
 
 class MeasureErrorNo(object):
- """Error type for MeasureResult."""
+ """Error type for MeasureResult."""
 
  NO_ERROR = 0 # No error
  INSTANTIATION_ERROR = 1 # Errors happen when apply transform steps from init state

python/tvm/auto_scheduler/search_policy.py

@@ -96,7 +96,7 @@ def __init__(self, meet_condition_func, apply_func, rule_name="CustomSketchRule"
 
 @tvm._ffi.register_object("auto_scheduler.SearchPolicy")
 class SearchPolicy(Object):
- """The base class of search policies."""
+ """The base class of search policies."""
 
  def continue_search_one_round(self, num_measure, measurer):
  """

python/tvm/auto_scheduler/task_scheduler.py

@@ -540,7 +540,7 @@ def _restore_status(self, log_file, num_measures_per_round):
 
 
 class TaskSchedulerCallback:
- """The base class of task scheduler callback functions."""
+ """The base class of task scheduler callback functions."""
 
  def pre_tune(self, task_scheduler, task_id):
  """The callback before tuning each task.

python/tvm/auto_scheduler/utils.py

@@ -190,7 +190,7 @@ def get_const_tuple(in_tuple):
 
 
 def list_to_tuple(x):
- """Convert a list to a tuple recursively."""
+ """Convert a list to a tuple recursively."""
  assert isinstance(x, list)
  return tuple(list_to_tuple(y) if isinstance(y, list) else y for y in x)
 
@@ -250,7 +250,7 @@ def kill_child_processes(parent_pid, sig=signal.SIGTERM):
 
 
 def make_traceback_info():
- """Get the error message from traceback."""
+ """Get the error message from traceback."""
  info = str(traceback.format_exc())
  if len(info) > MAX_TRACEBACK_INFO_LEN:
  info = (

python/tvm/contrib/cc.py

@@ -92,7 +92,7 @@ def get_target_by_dump_machine(compiler):
  """
 
  def get_target_triple():
- """Get target triple according to dumpmachine option of compiler."""
+ """Get target triple according to dumpmachine option of compiler."""
  if compiler:
  cmd = [compiler, "-dumpmachine"]
  proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)

python/tvm/contrib/peak.py

@@ -26,7 +26,7 @@
 
 
 def _convert_to_remote(func, remote):
- """convert module function to remote rpc function"""
+ """convert module function to remote rpc function"""
  temp = utils.tempdir()
  path_dso = temp.relpath("tmp_func.tar")
  func.export_library(path_dso)

python/tvm/contrib/tedd.py

@@ -147,7 +147,7 @@ def get_itervar_label_color(itervar, iv_type):
 
 
 def linebrk(s, n):
- """Break input string s with <br/> for every n charactors."""
+ """Break input string s with <br/> for every n charactors."""
  result = ""
  j = 0
  for i, c in enumerate(s):

python/tvm/driver/tvmc/autotuner.py

@@ -46,7 +46,7 @@
 
 @register_parser
 def add_tune_parser(subparsers):
- """Include parser for 'tune' subcommand"""
+ """Include parser for 'tune' subcommand"""
 
  parser = subparsers.add_parser("tune", help="auto-tune a model")
  parser.set_defaults(func=drive_tune)

python/tvm/driver/tvmc/frontends.py

@@ -77,7 +77,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 def import_keras():
- """Lazy import function for Keras"""
+ """Lazy import function for Keras"""
  # Keras writes the message "Using TensorFlow backend." to stderr
  # Redirect stderr during the import to disable this
  stderr = sys.stderr
@@ -93,7 +93,7 @@ def import_keras():
 
 
 class KerasFrontend(Frontend):
- """Keras frontend for TVMC"""
+ """Keras frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -151,7 +151,7 @@ def sequential_to_functional(self, model):
 
 
 class OnnxFrontend(Frontend):
- """ONNX frontend for TVMC"""
+ """ONNX frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -172,7 +172,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class TensorflowFrontend(Frontend):
- """TensorFlow frontend for TVMC"""
+ """TensorFlow frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -199,7 +199,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class TFLiteFrontend(Frontend):
- """TFLite frontend for TVMC"""
+ """TFLite frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -237,7 +237,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class PyTorchFrontend(Frontend):
- """PyTorch frontend for TVMC"""
+ """PyTorch frontend for TVMC"""
 
  @staticmethod
  def name():

python/tvm/driver/tvmc/main.py

@@ -53,7 +53,7 @@ def _example_parser(main_subparser):
 
 
 def _main(argv):
- """TVM command line interface."""
+ """TVM command line interface."""
 
  parser = argparse.ArgumentParser(
  prog="tvmc",

python/tvm/relay/analysis/feature.py

@@ -20,7 +20,7 @@
 
 
 class Feature(IntEnum):
- """The features a program might contain."""
+ """The features a program might contain."""
 
  fVar = 0
  fGlobalVar = 1

python/tvm/relay/backend/executor_factory.py

@@ -31,7 +31,7 @@ class ExecutorFactoryModule:
 
  @abstractmethod
  def get_executor_config(self):
- """Return the internal configuration the executor uses to execute the network"""
+ """Return the internal configuration the executor uses to execute the network"""
  raise NotImplementedError
 
  @abstractmethod
@@ -41,7 +41,7 @@ def get_params(self):
 
  @abstractmethod
  def get_lib(self):
- """Return the generated library"""
+ """Return the generated library"""
  raise NotImplementedError
 
  def __getitem__(self, item):

apps/extension/python/tvm_ext/__init__.py

@@ -44,7 +44,7 @@ def load_lib():
 
 @tvm.register_object("tvm_ext.IntVector")
 class IntVec(tvm.Object):
- """Example for using extension class in c++"""
+ """Example for using extension class in c++"""
 
  @property
  def _tvm_handle(self):

python/tvm/_ffi/_ctypes/packed_func.py

@@ -73,7 +73,7 @@ def convert_to_tvm_func(pyfunc):
  local_pyfunc = pyfunc
 
  def cfun(args, type_codes, num_args, ret, _):
- """ctypes function"""
+ """ctypes function"""
  num_args = num_args.value if isinstance(num_args, ctypes.c_int) else num_args
  pyargs = (C_TO_PY_ARG_SWITCH[type_codes[i]](args[i]) for i in range(num_args))
  # pylint: disable=broad-except

python/tvm/arith/analyzer.py

@@ -22,7 +22,7 @@
 
 @tvm._ffi.register_object("arith.ModularSet")
 class ModularSet(Object):
- """Represent range of (coeff * x + base) for x in Z"""
+ """Represent range of (coeff * x + base) for x in Z"""
 
  def __init__(self, coeff, base):
  self.__init_handle_by_constructor__(_ffi_api.ModularSet, coeff, base)

python/tvm/auto_scheduler/loop_state.py

@@ -48,12 +48,12 @@
 
 @tvm._ffi.register_object("auto_scheduler.Iterator")
 class Iterator(Object):
- """A loop iterator structure."""
+ """A loop iterator structure."""
 
 
 @tvm._ffi.register_object("auto_scheduler.Stage")
 class Stage(Object):
- """A stage in the compute declaration. Similar to tvm.te.schedule.Stage."""
+ """A stage in the compute declaration. Similar to tvm.te.schedule.Stage."""
 
  # Static trans table for compute_at location
  # This is used to transform the compute_at location to C++ enum
@@ -62,7 +62,7 @@ class Stage(Object):
 
 @tvm._ffi.register_object("auto_scheduler.State")
 class StateObject(Object):
- """The internal State object"""
+ """The internal State object"""
 
  def __eq__(self, other):
  return _ffi_api.StateEqual(self, other)
@@ -579,7 +579,7 @@ def rfactor(self, stage, iterator, factor_iter_id):
  return self.stages[int(new_stage_id)].op
 
  def copy(self):
- """Do deep copy of this State."""
+ """Do deep copy of this State."""
  state = State(self.state_object, self.compute_dag)
  state.stage_id_map = self.stage_id_map.copy()
  return state

python/tvm/auto_scheduler/measure.py

@@ -84,7 +84,7 @@ class BuildFunc:
 
 @tvm._ffi.register_object("auto_scheduler.MeasureCallback")
 class MeasureCallback(Object):
- """The base class of measurement callback functions."""
+ """The base class of measurement callback functions."""
 
 
 @tvm._ffi.register_object("auto_scheduler.PythonBasedMeasureCallback")
@@ -244,7 +244,7 @@ def recover_measure_input(inp, rebuild_state=False):
 
 @tvm._ffi.register_object("auto_scheduler.ProgramBuilder")
 class ProgramBuilder(Object):
- """The base class of ProgramBuilders."""
+ """The base class of ProgramBuilders."""
 
  def build(self, measure_inputs, verbose=1):
  """Build programs and return results.
@@ -265,7 +265,7 @@ def build(self, measure_inputs, verbose=1):
 
 @tvm._ffi.register_object("auto_scheduler.ProgramRunner")
 class ProgramRunner(Object):
- """The base class of ProgramRunners."""
+ """The base class of ProgramRunners."""
 
  def run(self, measure_inputs, build_results, verbose=1):
  """Run measurement and return results.
@@ -585,7 +585,7 @@ def __del__(self):
 
 
 class MeasureErrorNo(object):
- """Error type for MeasureResult."""
+ """Error type for MeasureResult."""
 
  NO_ERROR = 0 # No error
  INSTANTIATION_ERROR = 1 # Errors happen when apply transform steps from init state

python/tvm/auto_scheduler/search_policy.py

@@ -96,7 +96,7 @@ def __init__(self, meet_condition_func, apply_func, rule_name="CustomSketchRule"
 
 @tvm._ffi.register_object("auto_scheduler.SearchPolicy")
 class SearchPolicy(Object):
- """The base class of search policies."""
+ """The base class of search policies."""
 
  def continue_search_one_round(self, num_measure, measurer):
  """

python/tvm/auto_scheduler/task_scheduler.py

@@ -540,7 +540,7 @@ def _restore_status(self, log_file, num_measures_per_round):
 
 
 class TaskSchedulerCallback:
- """The base class of task scheduler callback functions."""
+ """The base class of task scheduler callback functions."""
 
  def pre_tune(self, task_scheduler, task_id):
  """The callback before tuning each task.

python/tvm/auto_scheduler/utils.py

@@ -190,7 +190,7 @@ def get_const_tuple(in_tuple):
 
 
 def list_to_tuple(x):
- """Convert a list to a tuple recursively."""
+ """Convert a list to a tuple recursively."""
  assert isinstance(x, list)
  return tuple(list_to_tuple(y) if isinstance(y, list) else y for y in x)
 
@@ -250,7 +250,7 @@ def kill_child_processes(parent_pid, sig=signal.SIGTERM):
 
 
 def make_traceback_info():
- """Get the error message from traceback."""
+ """Get the error message from traceback."""
  info = str(traceback.format_exc())
  if len(info) > MAX_TRACEBACK_INFO_LEN:
  info = (

python/tvm/contrib/cc.py

@@ -92,7 +92,7 @@ def get_target_by_dump_machine(compiler):
  """
 
  def get_target_triple():
- """Get target triple according to dumpmachine option of compiler."""
+ """Get target triple according to dumpmachine option of compiler."""
  if compiler:
  cmd = [compiler, "-dumpmachine"]
  proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)

python/tvm/contrib/peak.py

@@ -26,7 +26,7 @@
 
 
 def _convert_to_remote(func, remote):
- """convert module function to remote rpc function"""
+ """convert module function to remote rpc function"""
  temp = utils.tempdir()
  path_dso = temp.relpath("tmp_func.tar")
  func.export_library(path_dso)

python/tvm/contrib/tedd.py

@@ -147,7 +147,7 @@ def get_itervar_label_color(itervar, iv_type):
 
 
 def linebrk(s, n):
- """Break input string s with <br/> for every n charactors."""
+ """Break input string s with <br/> for every n charactors."""
  result = ""
  j = 0
  for i, c in enumerate(s):

python/tvm/driver/tvmc/autotuner.py

@@ -46,7 +46,7 @@
 
 @register_parser
 def add_tune_parser(subparsers):
- """Include parser for 'tune' subcommand"""
+ """Include parser for 'tune' subcommand"""
 
  parser = subparsers.add_parser("tune", help="auto-tune a model")
  parser.set_defaults(func=drive_tune)

python/tvm/driver/tvmc/frontends.py

@@ -77,7 +77,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 def import_keras():
- """Lazy import function for Keras"""
+ """Lazy import function for Keras"""
  # Keras writes the message "Using TensorFlow backend." to stderr
  # Redirect stderr during the import to disable this
  stderr = sys.stderr
@@ -93,7 +93,7 @@ def import_keras():
 
 
 class KerasFrontend(Frontend):
- """Keras frontend for TVMC"""
+ """Keras frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -151,7 +151,7 @@ def sequential_to_functional(self, model):
 
 
 class OnnxFrontend(Frontend):
- """ONNX frontend for TVMC"""
+ """ONNX frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -172,7 +172,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class TensorflowFrontend(Frontend):
- """TensorFlow frontend for TVMC"""
+ """TensorFlow frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -199,7 +199,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class TFLiteFrontend(Frontend):
- """TFLite frontend for TVMC"""
+ """TFLite frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -237,7 +237,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class PyTorchFrontend(Frontend):
- """PyTorch frontend for TVMC"""
+ """PyTorch frontend for TVMC"""
 
  @staticmethod
  def name():

python/tvm/driver/tvmc/main.py

@@ -53,7 +53,7 @@ def _example_parser(main_subparser):
 
 
 def _main(argv):
- """TVM command line interface."""
+ """TVM command line interface."""
 
  parser = argparse.ArgumentParser(
  prog="tvmc",

python/tvm/relay/analysis/feature.py

@@ -20,7 +20,7 @@
 
 
 class Feature(IntEnum):
- """The features a program might contain."""
+ """The features a program might contain."""
 
  fVar = 0
  fGlobalVar = 1

python/tvm/relay/backend/executor_factory.py

@@ -31,7 +31,7 @@ class ExecutorFactoryModule:
 
  @abstractmethod
  def get_executor_config(self):
- """Return the internal configuration the executor uses to execute the network"""
+ """Return the internal configuration the executor uses to execute the network"""
  raise NotImplementedError
 
  @abstractmethod
@@ -41,7 +41,7 @@ def get_params(self):
 
  @abstractmethod
  def get_lib(self):
- """Return the generated library"""
+ """Return the generated library"""
  raise NotImplementedError
 
  def __getitem__(self, item):

apps/extension/python/tvm_ext/__init__.py

@@ -44,7 +44,7 @@ def load_lib():
 
 @tvm.register_object("tvm_ext.IntVector")
 class IntVec(tvm.Object):
- """Example for using extension class in c++"""
+ """Example for using extension class in c++"""
 
  @property
  def _tvm_handle(self):

python/tvm/_ffi/_ctypes/packed_func.py

@@ -73,7 +73,7 @@ def convert_to_tvm_func(pyfunc):
  local_pyfunc = pyfunc
 
  def cfun(args, type_codes, num_args, ret, _):
- """ctypes function"""
+ """ctypes function"""
  num_args = num_args.value if isinstance(num_args, ctypes.c_int) else num_args
  pyargs = (C_TO_PY_ARG_SWITCH[type_codes[i]](args[i]) for i in range(num_args))
  # pylint: disable=broad-except

python/tvm/arith/analyzer.py

@@ -22,7 +22,7 @@
 
 @tvm._ffi.register_object("arith.ModularSet")
 class ModularSet(Object):
- """Represent range of (coeff * x + base) for x in Z"""
+ """Represent range of (coeff * x + base) for x in Z"""
 
  def __init__(self, coeff, base):
  self.__init_handle_by_constructor__(_ffi_api.ModularSet, coeff, base)

python/tvm/auto_scheduler/loop_state.py

@@ -48,12 +48,12 @@
 
 @tvm._ffi.register_object("auto_scheduler.Iterator")
 class Iterator(Object):
- """A loop iterator structure."""
+ """A loop iterator structure."""
 
 
 @tvm._ffi.register_object("auto_scheduler.Stage")
 class Stage(Object):
- """A stage in the compute declaration. Similar to tvm.te.schedule.Stage."""
+ """A stage in the compute declaration. Similar to tvm.te.schedule.Stage."""
 
  # Static trans table for compute_at location
  # This is used to transform the compute_at location to C++ enum
@@ -62,7 +62,7 @@ class Stage(Object):
 
 @tvm._ffi.register_object("auto_scheduler.State")
 class StateObject(Object):
- """The internal State object"""
+ """The internal State object"""
 
  def __eq__(self, other):
  return _ffi_api.StateEqual(self, other)
@@ -579,7 +579,7 @@ def rfactor(self, stage, iterator, factor_iter_id):
  return self.stages[int(new_stage_id)].op
 
  def copy(self):
- """Do deep copy of this State."""
+ """Do deep copy of this State."""
  state = State(self.state_object, self.compute_dag)
  state.stage_id_map = self.stage_id_map.copy()
  return state

python/tvm/auto_scheduler/measure.py

@@ -84,7 +84,7 @@ class BuildFunc:
 
 @tvm._ffi.register_object("auto_scheduler.MeasureCallback")
 class MeasureCallback(Object):
- """The base class of measurement callback functions."""
+ """The base class of measurement callback functions."""
 
 
 @tvm._ffi.register_object("auto_scheduler.PythonBasedMeasureCallback")
@@ -244,7 +244,7 @@ def recover_measure_input(inp, rebuild_state=False):
 
 @tvm._ffi.register_object("auto_scheduler.ProgramBuilder")
 class ProgramBuilder(Object):
- """The base class of ProgramBuilders."""
+ """The base class of ProgramBuilders."""
 
  def build(self, measure_inputs, verbose=1):
  """Build programs and return results.
@@ -265,7 +265,7 @@ def build(self, measure_inputs, verbose=1):
 
 @tvm._ffi.register_object("auto_scheduler.ProgramRunner")
 class ProgramRunner(Object):
- """The base class of ProgramRunners."""
+ """The base class of ProgramRunners."""
 
  def run(self, measure_inputs, build_results, verbose=1):
  """Run measurement and return results.
@@ -585,7 +585,7 @@ def __del__(self):
 
 
 class MeasureErrorNo(object):
- """Error type for MeasureResult."""
+ """Error type for MeasureResult."""
 
  NO_ERROR = 0 # No error
  INSTANTIATION_ERROR = 1 # Errors happen when apply transform steps from init state

python/tvm/auto_scheduler/search_policy.py

@@ -96,7 +96,7 @@ def __init__(self, meet_condition_func, apply_func, rule_name="CustomSketchRule"
 
 @tvm._ffi.register_object("auto_scheduler.SearchPolicy")
 class SearchPolicy(Object):
- """The base class of search policies."""
+ """The base class of search policies."""
 
  def continue_search_one_round(self, num_measure, measurer):
  """

python/tvm/auto_scheduler/task_scheduler.py

@@ -540,7 +540,7 @@ def _restore_status(self, log_file, num_measures_per_round):
 
 
 class TaskSchedulerCallback:
- """The base class of task scheduler callback functions."""
+ """The base class of task scheduler callback functions."""
 
  def pre_tune(self, task_scheduler, task_id):
  """The callback before tuning each task.

python/tvm/auto_scheduler/utils.py

@@ -190,7 +190,7 @@ def get_const_tuple(in_tuple):
 
 
 def list_to_tuple(x):
- """Convert a list to a tuple recursively."""
+ """Convert a list to a tuple recursively."""
  assert isinstance(x, list)
  return tuple(list_to_tuple(y) if isinstance(y, list) else y for y in x)
 
@@ -250,7 +250,7 @@ def kill_child_processes(parent_pid, sig=signal.SIGTERM):
 
 
 def make_traceback_info():
- """Get the error message from traceback."""
+ """Get the error message from traceback."""
  info = str(traceback.format_exc())
  if len(info) > MAX_TRACEBACK_INFO_LEN:
  info = (

python/tvm/contrib/cc.py

@@ -92,7 +92,7 @@ def get_target_by_dump_machine(compiler):
  """
 
  def get_target_triple():
- """Get target triple according to dumpmachine option of compiler."""
+ """Get target triple according to dumpmachine option of compiler."""
  if compiler:
  cmd = [compiler, "-dumpmachine"]
  proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)

python/tvm/contrib/peak.py

@@ -26,7 +26,7 @@
 
 
 def _convert_to_remote(func, remote):
- """convert module function to remote rpc function"""
+ """convert module function to remote rpc function"""
  temp = utils.tempdir()
  path_dso = temp.relpath("tmp_func.tar")
  func.export_library(path_dso)

python/tvm/contrib/tedd.py

@@ -147,7 +147,7 @@ def get_itervar_label_color(itervar, iv_type):
 
 
 def linebrk(s, n):
- """Break input string s with <br/> for every n charactors."""
+ """Break input string s with <br/> for every n charactors."""
  result = ""
  j = 0
  for i, c in enumerate(s):

python/tvm/driver/tvmc/autotuner.py

@@ -46,7 +46,7 @@
 
 @register_parser
 def add_tune_parser(subparsers):
- """Include parser for 'tune' subcommand"""
+ """Include parser for 'tune' subcommand"""
 
  parser = subparsers.add_parser("tune", help="auto-tune a model")
  parser.set_defaults(func=drive_tune)

python/tvm/driver/tvmc/frontends.py

@@ -77,7 +77,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 def import_keras():
- """Lazy import function for Keras"""
+ """Lazy import function for Keras"""
  # Keras writes the message "Using TensorFlow backend." to stderr
  # Redirect stderr during the import to disable this
  stderr = sys.stderr
@@ -93,7 +93,7 @@ def import_keras():
 
 
 class KerasFrontend(Frontend):
- """Keras frontend for TVMC"""
+ """Keras frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -151,7 +151,7 @@ def sequential_to_functional(self, model):
 
 
 class OnnxFrontend(Frontend):
- """ONNX frontend for TVMC"""
+ """ONNX frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -172,7 +172,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class TensorflowFrontend(Frontend):
- """TensorFlow frontend for TVMC"""
+ """TensorFlow frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -199,7 +199,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class TFLiteFrontend(Frontend):
- """TFLite frontend for TVMC"""
+ """TFLite frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -237,7 +237,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class PyTorchFrontend(Frontend):
- """PyTorch frontend for TVMC"""
+ """PyTorch frontend for TVMC"""
 
  @staticmethod
  def name():

python/tvm/driver/tvmc/main.py

@@ -53,7 +53,7 @@ def _example_parser(main_subparser):
 
 
 def _main(argv):
- """TVM command line interface."""
+ """TVM command line interface."""
 
  parser = argparse.ArgumentParser(
  prog="tvmc",

python/tvm/relay/analysis/feature.py

@@ -20,7 +20,7 @@
 
 
 class Feature(IntEnum):
- """The features a program might contain."""
+ """The features a program might contain."""
 
  fVar = 0
  fGlobalVar = 1

python/tvm/relay/backend/executor_factory.py

@@ -31,7 +31,7 @@ class ExecutorFactoryModule:
 
  @abstractmethod
  def get_executor_config(self):
- """Return the internal configuration the executor uses to execute the network"""
+ """Return the internal configuration the executor uses to execute the network"""
  raise NotImplementedError
 
  @abstractmethod
@@ -41,7 +41,7 @@ def get_params(self):
 
  @abstractmethod
  def get_lib(self):
- """Return the generated library"""
+ """Return the generated library"""
  raise NotImplementedError
 
  def __getitem__(self, item):

apps/extension/python/tvm_ext/__init__.py

@@ -44,7 +44,7 @@ def load_lib():
 
 @tvm.register_object("tvm_ext.IntVector")
 class IntVec(tvm.Object):
- """Example for using extension class in c++"""
+ """Example for using extension class in c++"""
 
  @property
  def _tvm_handle(self):

python/tvm/_ffi/_ctypes/packed_func.py

@@ -73,7 +73,7 @@ def convert_to_tvm_func(pyfunc):
  local_pyfunc = pyfunc
 
  def cfun(args, type_codes, num_args, ret, _):
- """ctypes function"""
+ """ctypes function"""
  num_args = num_args.value if isinstance(num_args, ctypes.c_int) else num_args
  pyargs = (C_TO_PY_ARG_SWITCH[type_codes[i]](args[i]) for i in range(num_args))
  # pylint: disable=broad-except

python/tvm/arith/analyzer.py

@@ -22,7 +22,7 @@
 
 @tvm._ffi.register_object("arith.ModularSet")
 class ModularSet(Object):
- """Represent range of (coeff * x + base) for x in Z"""
+ """Represent range of (coeff * x + base) for x in Z"""
 
  def __init__(self, coeff, base):
  self.__init_handle_by_constructor__(_ffi_api.ModularSet, coeff, base)

python/tvm/auto_scheduler/loop_state.py

@@ -48,12 +48,12 @@
 
 @tvm._ffi.register_object("auto_scheduler.Iterator")
 class Iterator(Object):
- """A loop iterator structure."""
+ """A loop iterator structure."""
 
 
 @tvm._ffi.register_object("auto_scheduler.Stage")
 class Stage(Object):
- """A stage in the compute declaration. Similar to tvm.te.schedule.Stage."""
+ """A stage in the compute declaration. Similar to tvm.te.schedule.Stage."""
 
  # Static trans table for compute_at location
  # This is used to transform the compute_at location to C++ enum
@@ -62,7 +62,7 @@ class Stage(Object):
 
 @tvm._ffi.register_object("auto_scheduler.State")
 class StateObject(Object):
- """The internal State object"""
+ """The internal State object"""
 
  def __eq__(self, other):
  return _ffi_api.StateEqual(self, other)
@@ -579,7 +579,7 @@ def rfactor(self, stage, iterator, factor_iter_id):
  return self.stages[int(new_stage_id)].op
 
  def copy(self):
- """Do deep copy of this State."""
+ """Do deep copy of this State."""
  state = State(self.state_object, self.compute_dag)
  state.stage_id_map = self.stage_id_map.copy()
  return state

python/tvm/auto_scheduler/measure.py

@@ -84,7 +84,7 @@ class BuildFunc:
 
 @tvm._ffi.register_object("auto_scheduler.MeasureCallback")
 class MeasureCallback(Object):
- """The base class of measurement callback functions."""
+ """The base class of measurement callback functions."""
 
 
 @tvm._ffi.register_object("auto_scheduler.PythonBasedMeasureCallback")
@@ -244,7 +244,7 @@ def recover_measure_input(inp, rebuild_state=False):
 
 @tvm._ffi.register_object("auto_scheduler.ProgramBuilder")
 class ProgramBuilder(Object):
- """The base class of ProgramBuilders."""
+ """The base class of ProgramBuilders."""
 
  def build(self, measure_inputs, verbose=1):
  """Build programs and return results.
@@ -265,7 +265,7 @@ def build(self, measure_inputs, verbose=1):
 
 @tvm._ffi.register_object("auto_scheduler.ProgramRunner")
 class ProgramRunner(Object):
- """The base class of ProgramRunners."""
+ """The base class of ProgramRunners."""
 
  def run(self, measure_inputs, build_results, verbose=1):
  """Run measurement and return results.
@@ -585,7 +585,7 @@ def __del__(self):
 
 
 class MeasureErrorNo(object):
- """Error type for MeasureResult."""
+ """Error type for MeasureResult."""
 
  NO_ERROR = 0 # No error
  INSTANTIATION_ERROR = 1 # Errors happen when apply transform steps from init state

python/tvm/auto_scheduler/search_policy.py

@@ -96,7 +96,7 @@ def __init__(self, meet_condition_func, apply_func, rule_name="CustomSketchRule"
 
 @tvm._ffi.register_object("auto_scheduler.SearchPolicy")
 class SearchPolicy(Object):
- """The base class of search policies."""
+ """The base class of search policies."""
 
  def continue_search_one_round(self, num_measure, measurer):
  """

python/tvm/auto_scheduler/task_scheduler.py

@@ -540,7 +540,7 @@ def _restore_status(self, log_file, num_measures_per_round):
 
 
 class TaskSchedulerCallback:
- """The base class of task scheduler callback functions."""
+ """The base class of task scheduler callback functions."""
 
  def pre_tune(self, task_scheduler, task_id):
  """The callback before tuning each task.

python/tvm/auto_scheduler/utils.py

@@ -190,7 +190,7 @@ def get_const_tuple(in_tuple):
 
 
 def list_to_tuple(x):
- """Convert a list to a tuple recursively."""
+ """Convert a list to a tuple recursively."""
  assert isinstance(x, list)
  return tuple(list_to_tuple(y) if isinstance(y, list) else y for y in x)
 
@@ -250,7 +250,7 @@ def kill_child_processes(parent_pid, sig=signal.SIGTERM):
 
 
 def make_traceback_info():
- """Get the error message from traceback."""
+ """Get the error message from traceback."""
  info = str(traceback.format_exc())
  if len(info) > MAX_TRACEBACK_INFO_LEN:
  info = (

python/tvm/contrib/cc.py

@@ -92,7 +92,7 @@ def get_target_by_dump_machine(compiler):
  """
 
  def get_target_triple():
- """Get target triple according to dumpmachine option of compiler."""
+ """Get target triple according to dumpmachine option of compiler."""
  if compiler:
  cmd = [compiler, "-dumpmachine"]
  proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)

python/tvm/contrib/peak.py

@@ -26,7 +26,7 @@
 
 
 def _convert_to_remote(func, remote):
- """convert module function to remote rpc function"""
+ """convert module function to remote rpc function"""
  temp = utils.tempdir()
  path_dso = temp.relpath("tmp_func.tar")
  func.export_library(path_dso)

python/tvm/contrib/tedd.py

@@ -147,7 +147,7 @@ def get_itervar_label_color(itervar, iv_type):
 
 
 def linebrk(s, n):
- """Break input string s with <br/> for every n charactors."""
+ """Break input string s with <br/> for every n charactors."""
  result = ""
  j = 0
  for i, c in enumerate(s):

python/tvm/driver/tvmc/autotuner.py

@@ -46,7 +46,7 @@
 
 @register_parser
 def add_tune_parser(subparsers):
- """Include parser for 'tune' subcommand"""
+ """Include parser for 'tune' subcommand"""
 
  parser = subparsers.add_parser("tune", help="auto-tune a model")
  parser.set_defaults(func=drive_tune)

python/tvm/driver/tvmc/frontends.py

@@ -77,7 +77,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 def import_keras():
- """Lazy import function for Keras"""
+ """Lazy import function for Keras"""
  # Keras writes the message "Using TensorFlow backend." to stderr
  # Redirect stderr during the import to disable this
  stderr = sys.stderr
@@ -93,7 +93,7 @@ def import_keras():
 
 
 class KerasFrontend(Frontend):
- """Keras frontend for TVMC"""
+ """Keras frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -151,7 +151,7 @@ def sequential_to_functional(self, model):
 
 
 class OnnxFrontend(Frontend):
- """ONNX frontend for TVMC"""
+ """ONNX frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -172,7 +172,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class TensorflowFrontend(Frontend):
- """TensorFlow frontend for TVMC"""
+ """TensorFlow frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -199,7 +199,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class TFLiteFrontend(Frontend):
- """TFLite frontend for TVMC"""
+ """TFLite frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -237,7 +237,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class PyTorchFrontend(Frontend):
- """PyTorch frontend for TVMC"""
+ """PyTorch frontend for TVMC"""
 
  @staticmethod
  def name():

python/tvm/driver/tvmc/main.py

@@ -53,7 +53,7 @@ def _example_parser(main_subparser):
 
 
 def _main(argv):
- """TVM command line interface."""
+ """TVM command line interface."""
 
  parser = argparse.ArgumentParser(
  prog="tvmc",

python/tvm/relay/analysis/feature.py

@@ -20,7 +20,7 @@
 
 
 class Feature(IntEnum):
- """The features a program might contain."""
+ """The features a program might contain."""
 
  fVar = 0
  fGlobalVar = 1

python/tvm/relay/backend/executor_factory.py

@@ -31,7 +31,7 @@ class ExecutorFactoryModule:
 
  @abstractmethod
  def get_executor_config(self):
- """Return the internal configuration the executor uses to execute the network"""
+ """Return the internal configuration the executor uses to execute the network"""
  raise NotImplementedError
 
  @abstractmethod
@@ -41,7 +41,7 @@ def get_params(self):
 
  @abstractmethod
  def get_lib(self):
- """Return the generated library"""
+ """Return the generated library"""
  raise NotImplementedError
 
  def __getitem__(self, item):

apps/extension/python/tvm_ext/__init__.py

@@ -44,7 +44,7 @@ def load_lib():
 
 @tvm.register_object("tvm_ext.IntVector")
 class IntVec(tvm.Object):
- """Example for using extension class in c++"""
+ """Example for using extension class in c++"""
 
  @property
  def _tvm_handle(self):

python/tvm/_ffi/_ctypes/packed_func.py

@@ -73,7 +73,7 @@ def convert_to_tvm_func(pyfunc):
  local_pyfunc = pyfunc
 
  def cfun(args, type_codes, num_args, ret, _):
- """ctypes function"""
+ """ctypes function"""
  num_args = num_args.value if isinstance(num_args, ctypes.c_int) else num_args
  pyargs = (C_TO_PY_ARG_SWITCH[type_codes[i]](args[i]) for i in range(num_args))
  # pylint: disable=broad-except

python/tvm/arith/analyzer.py

@@ -22,7 +22,7 @@
 
 @tvm._ffi.register_object("arith.ModularSet")
 class ModularSet(Object):
- """Represent range of (coeff * x + base) for x in Z"""
+ """Represent range of (coeff * x + base) for x in Z"""
 
  def __init__(self, coeff, base):
  self.__init_handle_by_constructor__(_ffi_api.ModularSet, coeff, base)

python/tvm/auto_scheduler/loop_state.py

@@ -48,12 +48,12 @@
 
 @tvm._ffi.register_object("auto_scheduler.Iterator")
 class Iterator(Object):
- """A loop iterator structure."""
+ """A loop iterator structure."""
 
 
 @tvm._ffi.register_object("auto_scheduler.Stage")
 class Stage(Object):
- """A stage in the compute declaration. Similar to tvm.te.schedule.Stage."""
+ """A stage in the compute declaration. Similar to tvm.te.schedule.Stage."""
 
  # Static trans table for compute_at location
  # This is used to transform the compute_at location to C++ enum
@@ -62,7 +62,7 @@ class Stage(Object):
 
 @tvm._ffi.register_object("auto_scheduler.State")
 class StateObject(Object):
- """The internal State object"""
+ """The internal State object"""
 
  def __eq__(self, other):
  return _ffi_api.StateEqual(self, other)
@@ -579,7 +579,7 @@ def rfactor(self, stage, iterator, factor_iter_id):
  return self.stages[int(new_stage_id)].op
 
  def copy(self):
- """Do deep copy of this State."""
+ """Do deep copy of this State."""
  state = State(self.state_object, self.compute_dag)
  state.stage_id_map = self.stage_id_map.copy()
  return state

python/tvm/auto_scheduler/measure.py

@@ -84,7 +84,7 @@ class BuildFunc:
 
 @tvm._ffi.register_object("auto_scheduler.MeasureCallback")
 class MeasureCallback(Object):
- """The base class of measurement callback functions."""
+ """The base class of measurement callback functions."""
 
 
 @tvm._ffi.register_object("auto_scheduler.PythonBasedMeasureCallback")
@@ -244,7 +244,7 @@ def recover_measure_input(inp, rebuild_state=False):
 
 @tvm._ffi.register_object("auto_scheduler.ProgramBuilder")
 class ProgramBuilder(Object):
- """The base class of ProgramBuilders."""
+ """The base class of ProgramBuilders."""
 
  def build(self, measure_inputs, verbose=1):
  """Build programs and return results.
@@ -265,7 +265,7 @@ def build(self, measure_inputs, verbose=1):
 
 @tvm._ffi.register_object("auto_scheduler.ProgramRunner")
 class ProgramRunner(Object):
- """The base class of ProgramRunners."""
+ """The base class of ProgramRunners."""
 
  def run(self, measure_inputs, build_results, verbose=1):
  """Run measurement and return results.
@@ -585,7 +585,7 @@ def __del__(self):
 
 
 class MeasureErrorNo(object):
- """Error type for MeasureResult."""
+ """Error type for MeasureResult."""
 
  NO_ERROR = 0 # No error
  INSTANTIATION_ERROR = 1 # Errors happen when apply transform steps from init state

python/tvm/auto_scheduler/search_policy.py

@@ -96,7 +96,7 @@ def __init__(self, meet_condition_func, apply_func, rule_name="CustomSketchRule"
 
 @tvm._ffi.register_object("auto_scheduler.SearchPolicy")
 class SearchPolicy(Object):
- """The base class of search policies."""
+ """The base class of search policies."""
 
  def continue_search_one_round(self, num_measure, measurer):
  """

python/tvm/auto_scheduler/task_scheduler.py

@@ -540,7 +540,7 @@ def _restore_status(self, log_file, num_measures_per_round):
 
 
 class TaskSchedulerCallback:
- """The base class of task scheduler callback functions."""
+ """The base class of task scheduler callback functions."""
 
  def pre_tune(self, task_scheduler, task_id):
  """The callback before tuning each task.

python/tvm/auto_scheduler/utils.py

@@ -190,7 +190,7 @@ def get_const_tuple(in_tuple):
 
 
 def list_to_tuple(x):
- """Convert a list to a tuple recursively."""
+ """Convert a list to a tuple recursively."""
  assert isinstance(x, list)
  return tuple(list_to_tuple(y) if isinstance(y, list) else y for y in x)
 
@@ -250,7 +250,7 @@ def kill_child_processes(parent_pid, sig=signal.SIGTERM):
 
 
 def make_traceback_info():
- """Get the error message from traceback."""
+ """Get the error message from traceback."""
  info = str(traceback.format_exc())
  if len(info) > MAX_TRACEBACK_INFO_LEN:
  info = (

python/tvm/contrib/cc.py

@@ -92,7 +92,7 @@ def get_target_by_dump_machine(compiler):
  """
 
  def get_target_triple():
- """Get target triple according to dumpmachine option of compiler."""
+ """Get target triple according to dumpmachine option of compiler."""
  if compiler:
  cmd = [compiler, "-dumpmachine"]
  proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)

python/tvm/contrib/peak.py

@@ -26,7 +26,7 @@
 
 
 def _convert_to_remote(func, remote):
- """convert module function to remote rpc function"""
+ """convert module function to remote rpc function"""
  temp = utils.tempdir()
  path_dso = temp.relpath("tmp_func.tar")
  func.export_library(path_dso)

python/tvm/contrib/tedd.py

@@ -147,7 +147,7 @@ def get_itervar_label_color(itervar, iv_type):
 
 
 def linebrk(s, n):
- """Break input string s with <br/> for every n charactors."""
+ """Break input string s with <br/> for every n charactors."""
  result = ""
  j = 0
  for i, c in enumerate(s):

python/tvm/driver/tvmc/autotuner.py

@@ -46,7 +46,7 @@
 
 @register_parser
 def add_tune_parser(subparsers):
- """Include parser for 'tune' subcommand"""
+ """Include parser for 'tune' subcommand"""
 
  parser = subparsers.add_parser("tune", help="auto-tune a model")
  parser.set_defaults(func=drive_tune)

python/tvm/driver/tvmc/frontends.py

@@ -77,7 +77,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 def import_keras():
- """Lazy import function for Keras"""
+ """Lazy import function for Keras"""
  # Keras writes the message "Using TensorFlow backend." to stderr
  # Redirect stderr during the import to disable this
  stderr = sys.stderr
@@ -93,7 +93,7 @@ def import_keras():
 
 
 class KerasFrontend(Frontend):
- """Keras frontend for TVMC"""
+ """Keras frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -151,7 +151,7 @@ def sequential_to_functional(self, model):
 
 
 class OnnxFrontend(Frontend):
- """ONNX frontend for TVMC"""
+ """ONNX frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -172,7 +172,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class TensorflowFrontend(Frontend):
- """TensorFlow frontend for TVMC"""
+ """TensorFlow frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -199,7 +199,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class TFLiteFrontend(Frontend):
- """TFLite frontend for TVMC"""
+ """TFLite frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -237,7 +237,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class PyTorchFrontend(Frontend):
- """PyTorch frontend for TVMC"""
+ """PyTorch frontend for TVMC"""
 
  @staticmethod
  def name():

python/tvm/driver/tvmc/main.py

@@ -53,7 +53,7 @@ def _example_parser(main_subparser):
 
 
 def _main(argv):
- """TVM command line interface."""
+ """TVM command line interface."""
 
  parser = argparse.ArgumentParser(
  prog="tvmc",

python/tvm/relay/analysis/feature.py

@@ -20,7 +20,7 @@
 
 
 class Feature(IntEnum):
- """The features a program might contain."""
+ """The features a program might contain."""
 
  fVar = 0
  fGlobalVar = 1

python/tvm/relay/backend/executor_factory.py

@@ -31,7 +31,7 @@ class ExecutorFactoryModule:
 
  @abstractmethod
  def get_executor_config(self):
- """Return the internal configuration the executor uses to execute the network"""
+ """Return the internal configuration the executor uses to execute the network"""
  raise NotImplementedError
 
  @abstractmethod
@@ -41,7 +41,7 @@ def get_params(self):
 
  @abstractmethod
  def get_lib(self):
- """Return the generated library"""
+ """Return the generated library"""
  raise NotImplementedError
 
  def __getitem__(self, item):

apps/extension/python/tvm_ext/__init__.py

@@ -44,7 +44,7 @@ def load_lib():
 
 @tvm.register_object("tvm_ext.IntVector")
 class IntVec(tvm.Object):
- """Example for using extension class in c++"""
+ """Example for using extension class in c++"""
 
  @property
  def _tvm_handle(self):

python/tvm/_ffi/_ctypes/packed_func.py

@@ -73,7 +73,7 @@ def convert_to_tvm_func(pyfunc):
  local_pyfunc = pyfunc
 
  def cfun(args, type_codes, num_args, ret, _):
- """ctypes function"""
+ """ctypes function"""
  num_args = num_args.value if isinstance(num_args, ctypes.c_int) else num_args
  pyargs = (C_TO_PY_ARG_SWITCH[type_codes[i]](args[i]) for i in range(num_args))
  # pylint: disable=broad-except

python/tvm/arith/analyzer.py

@@ -22,7 +22,7 @@
 
 @tvm._ffi.register_object("arith.ModularSet")
 class ModularSet(Object):
- """Represent range of (coeff * x + base) for x in Z"""
+ """Represent range of (coeff * x + base) for x in Z"""
 
  def __init__(self, coeff, base):
  self.__init_handle_by_constructor__(_ffi_api.ModularSet, coeff, base)

python/tvm/auto_scheduler/loop_state.py

@@ -48,12 +48,12 @@
 
 @tvm._ffi.register_object("auto_scheduler.Iterator")
 class Iterator(Object):
- """A loop iterator structure."""
+ """A loop iterator structure."""
 
 
 @tvm._ffi.register_object("auto_scheduler.Stage")
 class Stage(Object):
- """A stage in the compute declaration. Similar to tvm.te.schedule.Stage."""
+ """A stage in the compute declaration. Similar to tvm.te.schedule.Stage."""
 
  # Static trans table for compute_at location
  # This is used to transform the compute_at location to C++ enum
@@ -62,7 +62,7 @@ class Stage(Object):
 
 @tvm._ffi.register_object("auto_scheduler.State")
 class StateObject(Object):
- """The internal State object"""
+ """The internal State object"""
 
  def __eq__(self, other):
  return _ffi_api.StateEqual(self, other)
@@ -579,7 +579,7 @@ def rfactor(self, stage, iterator, factor_iter_id):
  return self.stages[int(new_stage_id)].op
 
  def copy(self):
- """Do deep copy of this State."""
+ """Do deep copy of this State."""
  state = State(self.state_object, self.compute_dag)
  state.stage_id_map = self.stage_id_map.copy()
  return state

python/tvm/auto_scheduler/measure.py

@@ -84,7 +84,7 @@ class BuildFunc:
 
 @tvm._ffi.register_object("auto_scheduler.MeasureCallback")
 class MeasureCallback(Object):
- """The base class of measurement callback functions."""
+ """The base class of measurement callback functions."""
 
 
 @tvm._ffi.register_object("auto_scheduler.PythonBasedMeasureCallback")
@@ -244,7 +244,7 @@ def recover_measure_input(inp, rebuild_state=False):
 
 @tvm._ffi.register_object("auto_scheduler.ProgramBuilder")
 class ProgramBuilder(Object):
- """The base class of ProgramBuilders."""
+ """The base class of ProgramBuilders."""
 
  def build(self, measure_inputs, verbose=1):
  """Build programs and return results.
@@ -265,7 +265,7 @@ def build(self, measure_inputs, verbose=1):
 
 @tvm._ffi.register_object("auto_scheduler.ProgramRunner")
 class ProgramRunner(Object):
- """The base class of ProgramRunners."""
+ """The base class of ProgramRunners."""
 
  def run(self, measure_inputs, build_results, verbose=1):
  """Run measurement and return results.
@@ -585,7 +585,7 @@ def __del__(self):
 
 
 class MeasureErrorNo(object):
- """Error type for MeasureResult."""
+ """Error type for MeasureResult."""
 
  NO_ERROR = 0 # No error
  INSTANTIATION_ERROR = 1 # Errors happen when apply transform steps from init state

python/tvm/auto_scheduler/search_policy.py

@@ -96,7 +96,7 @@ def __init__(self, meet_condition_func, apply_func, rule_name="CustomSketchRule"
 
 @tvm._ffi.register_object("auto_scheduler.SearchPolicy")
 class SearchPolicy(Object):
- """The base class of search policies."""
+ """The base class of search policies."""
 
  def continue_search_one_round(self, num_measure, measurer):
  """

python/tvm/auto_scheduler/task_scheduler.py

@@ -540,7 +540,7 @@ def _restore_status(self, log_file, num_measures_per_round):
 
 
 class TaskSchedulerCallback:
- """The base class of task scheduler callback functions."""
+ """The base class of task scheduler callback functions."""
 
  def pre_tune(self, task_scheduler, task_id):
  """The callback before tuning each task.

python/tvm/auto_scheduler/utils.py

@@ -190,7 +190,7 @@ def get_const_tuple(in_tuple):
 
 
 def list_to_tuple(x):
- """Convert a list to a tuple recursively."""
+ """Convert a list to a tuple recursively."""
  assert isinstance(x, list)
  return tuple(list_to_tuple(y) if isinstance(y, list) else y for y in x)
 
@@ -250,7 +250,7 @@ def kill_child_processes(parent_pid, sig=signal.SIGTERM):
 
 
 def make_traceback_info():
- """Get the error message from traceback."""
+ """Get the error message from traceback."""
  info = str(traceback.format_exc())
  if len(info) > MAX_TRACEBACK_INFO_LEN:
  info = (

python/tvm/contrib/cc.py

@@ -92,7 +92,7 @@ def get_target_by_dump_machine(compiler):
  """
 
  def get_target_triple():
- """Get target triple according to dumpmachine option of compiler."""
+ """Get target triple according to dumpmachine option of compiler."""
  if compiler:
  cmd = [compiler, "-dumpmachine"]
  proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)

python/tvm/contrib/peak.py

@@ -26,7 +26,7 @@
 
 
 def _convert_to_remote(func, remote):
- """convert module function to remote rpc function"""
+ """convert module function to remote rpc function"""
  temp = utils.tempdir()
  path_dso = temp.relpath("tmp_func.tar")
  func.export_library(path_dso)

python/tvm/contrib/tedd.py

@@ -147,7 +147,7 @@ def get_itervar_label_color(itervar, iv_type):
 
 
 def linebrk(s, n):
- """Break input string s with <br/> for every n charactors."""
+ """Break input string s with <br/> for every n charactors."""
  result = ""
  j = 0
  for i, c in enumerate(s):

python/tvm/driver/tvmc/autotuner.py

@@ -46,7 +46,7 @@
 
 @register_parser
 def add_tune_parser(subparsers):
- """Include parser for 'tune' subcommand"""
+ """Include parser for 'tune' subcommand"""
 
  parser = subparsers.add_parser("tune", help="auto-tune a model")
  parser.set_defaults(func=drive_tune)

python/tvm/driver/tvmc/frontends.py

@@ -77,7 +77,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 def import_keras():
- """Lazy import function for Keras"""
+ """Lazy import function for Keras"""
  # Keras writes the message "Using TensorFlow backend." to stderr
  # Redirect stderr during the import to disable this
  stderr = sys.stderr
@@ -93,7 +93,7 @@ def import_keras():
 
 
 class KerasFrontend(Frontend):
- """Keras frontend for TVMC"""
+ """Keras frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -151,7 +151,7 @@ def sequential_to_functional(self, model):
 
 
 class OnnxFrontend(Frontend):
- """ONNX frontend for TVMC"""
+ """ONNX frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -172,7 +172,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class TensorflowFrontend(Frontend):
- """TensorFlow frontend for TVMC"""
+ """TensorFlow frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -199,7 +199,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class TFLiteFrontend(Frontend):
- """TFLite frontend for TVMC"""
+ """TFLite frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -237,7 +237,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class PyTorchFrontend(Frontend):
- """PyTorch frontend for TVMC"""
+ """PyTorch frontend for TVMC"""
 
  @staticmethod
  def name():

python/tvm/driver/tvmc/main.py

@@ -53,7 +53,7 @@ def _example_parser(main_subparser):
 
 
 def _main(argv):
- """TVM command line interface."""
+ """TVM command line interface."""
 
  parser = argparse.ArgumentParser(
  prog="tvmc",

python/tvm/relay/analysis/feature.py

@@ -20,7 +20,7 @@
 
 
 class Feature(IntEnum):
- """The features a program might contain."""
+ """The features a program might contain."""
 
  fVar = 0
  fGlobalVar = 1

python/tvm/relay/backend/executor_factory.py

@@ -31,7 +31,7 @@ class ExecutorFactoryModule:
 
  @abstractmethod
  def get_executor_config(self):
- """Return the internal configuration the executor uses to execute the network"""
+ """Return the internal configuration the executor uses to execute the network"""
  raise NotImplementedError
 
  @abstractmethod
@@ -41,7 +41,7 @@ def get_params(self):
 
  @abstractmethod
  def get_lib(self):
- """Return the generated library"""
+ """Return the generated library"""
  raise NotImplementedError
 
  def __getitem__(self, item):

apps/extension/python/tvm_ext/__init__.py

@@ -44,7 +44,7 @@ def load_lib():
 
 @tvm.register_object("tvm_ext.IntVector")
 class IntVec(tvm.Object):
- """Example for using extension class in c++"""
+ """Example for using extension class in c++"""
 
  @property
  def _tvm_handle(self):

python/tvm/_ffi/_ctypes/packed_func.py

@@ -73,7 +73,7 @@ def convert_to_tvm_func(pyfunc):
  local_pyfunc = pyfunc
 
  def cfun(args, type_codes, num_args, ret, _):
- """ctypes function"""
+ """ctypes function"""
  num_args = num_args.value if isinstance(num_args, ctypes.c_int) else num_args
  pyargs = (C_TO_PY_ARG_SWITCH[type_codes[i]](args[i]) for i in range(num_args))
  # pylint: disable=broad-except

python/tvm/arith/analyzer.py

@@ -22,7 +22,7 @@
 
 @tvm._ffi.register_object("arith.ModularSet")
 class ModularSet(Object):
- """Represent range of (coeff * x + base) for x in Z"""
+ """Represent range of (coeff * x + base) for x in Z"""
 
  def __init__(self, coeff, base):
  self.__init_handle_by_constructor__(_ffi_api.ModularSet, coeff, base)

python/tvm/auto_scheduler/loop_state.py

@@ -48,12 +48,12 @@
 
 @tvm._ffi.register_object("auto_scheduler.Iterator")
 class Iterator(Object):
- """A loop iterator structure."""
+ """A loop iterator structure."""
 
 
 @tvm._ffi.register_object("auto_scheduler.Stage")
 class Stage(Object):
- """A stage in the compute declaration. Similar to tvm.te.schedule.Stage."""
+ """A stage in the compute declaration. Similar to tvm.te.schedule.Stage."""
 
  # Static trans table for compute_at location
  # This is used to transform the compute_at location to C++ enum
@@ -62,7 +62,7 @@ class Stage(Object):
 
 @tvm._ffi.register_object("auto_scheduler.State")
 class StateObject(Object):
- """The internal State object"""
+ """The internal State object"""
 
  def __eq__(self, other):
  return _ffi_api.StateEqual(self, other)
@@ -579,7 +579,7 @@ def rfactor(self, stage, iterator, factor_iter_id):
  return self.stages[int(new_stage_id)].op
 
  def copy(self):
- """Do deep copy of this State."""
+ """Do deep copy of this State."""
  state = State(self.state_object, self.compute_dag)
  state.stage_id_map = self.stage_id_map.copy()
  return state

python/tvm/auto_scheduler/measure.py

@@ -84,7 +84,7 @@ class BuildFunc:
 
 @tvm._ffi.register_object("auto_scheduler.MeasureCallback")
 class MeasureCallback(Object):
- """The base class of measurement callback functions."""
+ """The base class of measurement callback functions."""
 
 
 @tvm._ffi.register_object("auto_scheduler.PythonBasedMeasureCallback")
@@ -244,7 +244,7 @@ def recover_measure_input(inp, rebuild_state=False):
 
 @tvm._ffi.register_object("auto_scheduler.ProgramBuilder")
 class ProgramBuilder(Object):
- """The base class of ProgramBuilders."""
+ """The base class of ProgramBuilders."""
 
  def build(self, measure_inputs, verbose=1):
  """Build programs and return results.
@@ -265,7 +265,7 @@ def build(self, measure_inputs, verbose=1):
 
 @tvm._ffi.register_object("auto_scheduler.ProgramRunner")
 class ProgramRunner(Object):
- """The base class of ProgramRunners."""
+ """The base class of ProgramRunners."""
 
  def run(self, measure_inputs, build_results, verbose=1):
  """Run measurement and return results.
@@ -585,7 +585,7 @@ def __del__(self):
 
 
 class MeasureErrorNo(object):
- """Error type for MeasureResult."""
+ """Error type for MeasureResult."""
 
  NO_ERROR = 0 # No error
  INSTANTIATION_ERROR = 1 # Errors happen when apply transform steps from init state

python/tvm/auto_scheduler/search_policy.py

@@ -96,7 +96,7 @@ def __init__(self, meet_condition_func, apply_func, rule_name="CustomSketchRule"
 
 @tvm._ffi.register_object("auto_scheduler.SearchPolicy")
 class SearchPolicy(Object):
- """The base class of search policies."""
+ """The base class of search policies."""
 
  def continue_search_one_round(self, num_measure, measurer):
  """

python/tvm/auto_scheduler/task_scheduler.py

@@ -540,7 +540,7 @@ def _restore_status(self, log_file, num_measures_per_round):
 
 
 class TaskSchedulerCallback:
- """The base class of task scheduler callback functions."""
+ """The base class of task scheduler callback functions."""
 
  def pre_tune(self, task_scheduler, task_id):
  """The callback before tuning each task.

python/tvm/auto_scheduler/utils.py

@@ -190,7 +190,7 @@ def get_const_tuple(in_tuple):
 
 
 def list_to_tuple(x):
- """Convert a list to a tuple recursively."""
+ """Convert a list to a tuple recursively."""
  assert isinstance(x, list)
  return tuple(list_to_tuple(y) if isinstance(y, list) else y for y in x)
 
@@ -250,7 +250,7 @@ def kill_child_processes(parent_pid, sig=signal.SIGTERM):
 
 
 def make_traceback_info():
- """Get the error message from traceback."""
+ """Get the error message from traceback."""
  info = str(traceback.format_exc())
  if len(info) > MAX_TRACEBACK_INFO_LEN:
  info = (

python/tvm/contrib/cc.py

@@ -92,7 +92,7 @@ def get_target_by_dump_machine(compiler):
  """
 
  def get_target_triple():
- """Get target triple according to dumpmachine option of compiler."""
+ """Get target triple according to dumpmachine option of compiler."""
  if compiler:
  cmd = [compiler, "-dumpmachine"]
  proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)

python/tvm/contrib/peak.py

@@ -26,7 +26,7 @@
 
 
 def _convert_to_remote(func, remote):
- """convert module function to remote rpc function"""
+ """convert module function to remote rpc function"""
  temp = utils.tempdir()
  path_dso = temp.relpath("tmp_func.tar")
  func.export_library(path_dso)

python/tvm/contrib/tedd.py

@@ -147,7 +147,7 @@ def get_itervar_label_color(itervar, iv_type):
 
 
 def linebrk(s, n):
- """Break input string s with <br/> for every n charactors."""
+ """Break input string s with <br/> for every n charactors."""
  result = ""
  j = 0
  for i, c in enumerate(s):

python/tvm/driver/tvmc/autotuner.py

@@ -46,7 +46,7 @@
 
 @register_parser
 def add_tune_parser(subparsers):
- """Include parser for 'tune' subcommand"""
+ """Include parser for 'tune' subcommand"""
 
  parser = subparsers.add_parser("tune", help="auto-tune a model")
  parser.set_defaults(func=drive_tune)

python/tvm/driver/tvmc/frontends.py

@@ -77,7 +77,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 def import_keras():
- """Lazy import function for Keras"""
+ """Lazy import function for Keras"""
  # Keras writes the message "Using TensorFlow backend." to stderr
  # Redirect stderr during the import to disable this
  stderr = sys.stderr
@@ -93,7 +93,7 @@ def import_keras():
 
 
 class KerasFrontend(Frontend):
- """Keras frontend for TVMC"""
+ """Keras frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -151,7 +151,7 @@ def sequential_to_functional(self, model):
 
 
 class OnnxFrontend(Frontend):
- """ONNX frontend for TVMC"""
+ """ONNX frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -172,7 +172,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class TensorflowFrontend(Frontend):
- """TensorFlow frontend for TVMC"""
+ """TensorFlow frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -199,7 +199,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class TFLiteFrontend(Frontend):
- """TFLite frontend for TVMC"""
+ """TFLite frontend for TVMC"""
 
  @staticmethod
  def name():
@@ -237,7 +237,7 @@ def load(self, path, shape_dict=None, **kwargs):
 
 
 class PyTorchFrontend(Frontend):
- """PyTorch frontend for TVMC"""
+ """PyTorch frontend for TVMC"""
 
  @staticmethod
  def name():

python/tvm/driver/tvmc/main.py

@@ -53,7 +53,7 @@ def _example_parser(main_subparser):
 
 
 def _main(argv):
- """TVM command line interface."""
+ """TVM command line interface."""
 
  parser = argparse.ArgumentParser(
  prog="tvmc",

python/tvm/relay/analysis/feature.py

@@ -20,7 +20,7 @@
 
 
 class Feature(IntEnum):
- """The features a program might contain."""
+ """The features a program might contain."""
 
  fVar = 0
  fGlobalVar = 1

python/tvm/relay/backend/executor_factory.py

@@ -31,7 +31,7 @@ class ExecutorFactoryModule:
 
  @abstractmethod
  def get_executor_config(self):
- """Return the internal configuration the executor uses to execute the network"""
+ """Return the internal configuration the executor uses to execute the network"""
  raise NotImplementedError
 
  @abstractmethod
@@ -41,7 +41,7 @@ def get_params(self):
 
  @abstractmethod
  def get_lib(self):
- """Return the generated library"""
+ """Return the generated library"""
  raise NotImplementedError
 
  def __getitem__(self, item):