def testUIFactoryRaisesExceptionOnInvalidUITypeGivenAvailable(self):
with self.assertRaisesRegexp(ValueError,
"Invalid ui_type: 'readline'"):
ui_factory.get_ui("readline",
available_ui_types=["curses"],
config=cli_config.CLIConfig(
config_file_path=self._tmp_config_path))
def _launch_cli(self):
if self._is_run_start:
self.observers["run_start_cli_run_numbers"].append(
self._run_call_count)
else:
self.observers["run_end_cli_run_numbers"].append(
self._run_call_count)
readline_cli = ui_factory.get_ui("readline")
self._register_this_run_info(readline_cli)
while True:
command = self._command_sequence[self._command_pointer]
self._command_pointer += 1
try:
if command[0] == "run":
self._run_handler(command[1:])
elif command[0] == "print_feed":
self.observers["print_feed_responses"].append(
self._print_feed_handler(command[1:]))
else:
raise ValueError("Unrecognized command prefix: %s" %
command[0])
except debugger_cli_common.CommandLineExit as e:
return e.exit_token
def _launch_cli(self):
if self._is_run_start:
self.observers["run_start_cli_run_numbers"].append(self._run_call_count)
else:
self.observers["run_end_cli_run_numbers"].append(self._run_call_count)
readline_cli = ui_factory.get_ui(
"readline",
config=cli_config.CLIConfig(
config_file_path=os.path.join(tempfile.mkdtemp(), ".tfdbg_config")))
self._register_this_run_info(readline_cli)
while self._command_pointer < len(self._command_sequence):
command = self._command_sequence[self._command_pointer]
self._command_pointer += 1
try:
if command[0] == "run":
self._run_handler(command[1:])
elif command[0] == "print_feed":
self.observers["print_feed_responses"].append(
self._print_feed_handler(command[1:]))
else:
raise ValueError("Unrecognized command prefix: %s" % command[0])
except debugger_cli_common.CommandLineExit as e:
return e.exit_token
def create_profiler_ui(graph,
run_metadata,
ui_type="curses",
on_ui_exit=None):
"""Create an instance of CursesUI based on a `tf.Graph` and `RunMetadata`.
Args:
graph: Python `Graph` object.
run_metadata: A `RunMetadata` protobuf object.
ui_type: (str) requested UI type, e.g., "curses", "readline".
on_ui_exit: (`Callable`) the callback to be called when the UI exits.
Returns:
(base_ui.BaseUI) A BaseUI subtype object with a set of standard analyzer
commands and tab-completions registered.
"""
analyzer = ProfileAnalyzer(graph, run_metadata)
cli = ui_factory.get_ui(ui_type, on_ui_exit=on_ui_exit)
cli.register_command_handler(
"list_profile",
analyzer.list_profile,
analyzer.get_help("list_profile"),
prefix_aliases=["lp"])
cli.register_command_handler(
"print_source",
analyzer.print_source,
analyzer.get_help("print_source"),
prefix_aliases=["ps"])
return cli
def create_profiler_ui(graph,
run_metadata,
ui_type="curses",
on_ui_exit=None,
config=None):
"""Create an instance of CursesUI based on a `tf.Graph` and `RunMetadata`.
Args:
graph: Python `Graph` object.
run_metadata: A `RunMetadata` protobuf object.
ui_type: (str) requested UI type, e.g., "curses", "readline".
on_ui_exit: (`Callable`) the callback to be called when the UI exits.
config: An instance of `cli_config.CLIConfig`.
Returns:
(base_ui.BaseUI) A BaseUI subtype object with a set of standard analyzer
commands and tab-completions registered.
"""
del config # Currently unused.
analyzer = ProfileAnalyzer(graph, run_metadata)
cli = ui_factory.get_ui(ui_type, on_ui_exit=on_ui_exit)
cli.register_command_handler(
"list_profile",
analyzer.list_profile,
analyzer.get_help("list_profile"),
prefix_aliases=["lp"])
cli.register_command_handler(
"print_source",
analyzer.print_source,
analyzer.get_help("print_source"),
prefix_aliases=["ps"])
return cli
def create_analyzer_ui(debug_dump, tensor_filters=None, ui_type="curses"):
"""Create an instance of CursesUI based on a DebugDumpDir object.
Args:
debug_dump: (debug_data.DebugDumpDir) The debug dump to use.
tensor_filters: (dict) A dict mapping tensor filter name (str) to tensor
filter (Callable).
ui_type: (str) requested UI type, e.g., "curses", "readline".
Returns:
(base_ui.BaseUI) A BaseUI subtype object with a set of standard analyzer
commands and tab-completions registered.
"""
analyzer = DebugAnalyzer(debug_dump)
if tensor_filters:
for tensor_filter_name in tensor_filters:
analyzer.add_tensor_filter(
tensor_filter_name, tensor_filters[tensor_filter_name])
cli = ui_factory.get_ui(ui_type)
cli.register_command_handler(
"list_tensors",
analyzer.list_tensors,
analyzer.get_help("list_tensors"),
prefix_aliases=["lt"])
cli.register_command_handler(
"node_info",
analyzer.node_info,
analyzer.get_help("node_info"),
prefix_aliases=["ni"])
cli.register_command_handler(
"list_inputs",
analyzer.list_inputs,
analyzer.get_help("list_inputs"),
prefix_aliases=["li"])
cli.register_command_handler(
"list_outputs",
analyzer.list_outputs,
analyzer.get_help("list_outputs"),
prefix_aliases=["lo"])
cli.register_command_handler(
"print_tensor",
analyzer.print_tensor,
analyzer.get_help("print_tensor"),
prefix_aliases=["pt"])
cli.register_command_handler(
"print_source",
analyzer.print_source,
analyzer.get_help("print_source"),
prefix_aliases=["ps"])
dumped_tensor_names = []
for datum in debug_dump.dumped_tensor_data:
dumped_tensor_names.append("%s:%d" % (datum.node_name, datum.output_slot))
# Tab completions for command "print_tensors".
cli.register_tab_comp_context(["print_tensor", "pt"], dumped_tensor_names)
return cli
def _prep_cli_for_run_start(self):
"""Prepare (but not launch) the CLI for run-start."""
self._run_cli = ui_factory.get_ui(self._ui_type)
help_intro = debugger_cli_common.RichTextLines([])
if self._run_call_count == 1:
# Show logo at the onset of the first run.
help_intro.extend(cli_shared.get_tfdbg_logo())
help_intro.extend(debugger_cli_common.RichTextLines("Upcoming run:"))
help_intro.extend(self._run_info)
self._run_cli.set_help_intro(help_intro)
# Create initial screen output detailing the run.
self._title = "run-start: " + self._run_description
self._init_command = "run_info"
self._title_color = "blue_on_white"
def _prep_cli_for_run_start(self):
"""Prepare (but not launch) the CLI for run-start."""
self._run_cli = ui_factory.get_ui(self._ui_type)
help_intro = debugger_cli_common.RichTextLines([])
if self._run_call_count == 1:
# Show logo at the onset of the first run.
help_intro.extend(cli_shared.get_tfdbg_logo())
help_intro.extend(debugger_cli_common.RichTextLines("Upcoming run:"))
help_intro.extend(self._run_info)
self._run_cli.set_help_intro(help_intro)
# Create initial screen output detailing the run.
self._title = "run-start: " + self._run_description
self._init_command = "run_info"
self._title_color = "blue_on_white"
def _launch_cli(self):
if self._is_run_start:
self.observers["run_start_cli_run_numbers"].append(self._run_call_count)
else:
self.observers["run_end_cli_run_numbers"].append(self._run_call_count)
readline_cli = ui_factory.get_ui("readline")
self._register_this_run_info(readline_cli)
while True:
command = self._command_sequence[self._command_pointer]
self._command_pointer += 1
try:
if command[0] == "run":
self._run_handler(command[1:])
elif command[0] == "print_feed":
self.observers["print_feed_responses"].append(
self._print_feed_handler(command[1:]))
else:
raise ValueError("Unrecognized command prefix: %s" % command[0])
except debugger_cli_common.CommandLineExit as e:
return e.exit_token
def testUIFactoryCreatesReadlineUI(self):
ui = ui_factory.get_ui("readline")
self.assertIsInstance(ui, readline_ui.ReadlineUI)
def invoke_node_stepper(self,
node_stepper,
restore_variable_values_on_exit=True):
"""Overrides method in base class to implement interactive node stepper.
Args:
node_stepper: (`stepper.NodeStepper`) The underlying NodeStepper API
object.
restore_variable_values_on_exit: (`bool`) Whether any variables whose
values have been altered during this node-stepper invocation should be
restored to their old values when this invocation ends.
Returns:
The same return values as the `Session.run()` call on the same fetches as
the NodeStepper.
"""
stepper = stepper_cli.NodeStepperCLI(node_stepper)
# On exiting the node-stepper CLI, the finalize method of the node_stepper
# object will be called, ensuring that the state of the graph will be the
# same as if the stepping did not happen.
# TODO(cais): Perhaps some users will want the effect of the interactive
# stepping and value injection to persist. When that happens, make the call
# to finalize optional.
stepper_ui = ui_factory.get_ui(
self._ui_type,
on_ui_exit=(node_stepper.restore_variable_values
if restore_variable_values_on_exit else None))
stepper_ui.register_command_handler(
"list_sorted_nodes",
stepper.list_sorted_nodes,
stepper.arg_parsers["list_sorted_nodes"].format_help(),
prefix_aliases=["lt", "lsn"])
stepper_ui.register_command_handler(
"cont",
stepper.cont,
stepper.arg_parsers["cont"].format_help(),
prefix_aliases=["ct", "c"])
stepper_ui.register_command_handler(
"step",
stepper.step,
stepper.arg_parsers["step"].format_help(),
prefix_aliases=["st", "s"])
stepper_ui.register_command_handler(
"print_tensor",
stepper.print_tensor,
stepper.arg_parsers["print_tensor"].format_help(),
prefix_aliases=["pt"])
stepper_ui.register_command_handler(
"inject_value",
stepper.inject_value,
stepper.arg_parsers["inject_value"].format_help(),
prefix_aliases=["inject", "override_value", "override"])
# Register tab completion candidates.
stepper_ui.register_tab_comp_context([
"cont", "ct", "c", "pt", "inject_value", "inject",
"override_value", "override"
], [str(elem) for elem in node_stepper.sorted_nodes()])
# TODO(cais): Tie up register_tab_comp_context to a single alias to shorten
# calls like this.
return stepper_ui.run_ui(init_command="lt",
title="Node Stepper: " +
self._run_description,
title_color="blue_on_white")
def testUIFactoryRaisesExceptionOnInvalidUIType(self):
with self.assertRaisesRegex(ValueError, "Invalid ui_type: 'foobar'"):
ui_factory.get_ui(
"foobar",
config=cli_config.CLIConfig(config_file_path=self._tmp_config_path))
def testUIFactoryCreatesReadlineUI(self):
ui = ui_factory.get_ui(
"readline",
config=cli_config.CLIConfig(config_file_path=self._tmp_config_path))
self.assertIsInstance(ui, readline_ui.ReadlineUI)
def testUIFactoryRaisesExceptionOnInvalidUITypeGivenAvailable(self):
with self.assertRaisesRegexp(ValueError, "Invalid ui_type: 'readline'"):
ui_factory.get_ui("readline", available_ui_types=["curses"])
def testUIFactoryRaisesExceptionOnInvalidUIType(self):
with self.assertRaisesRegexp(ValueError, "Invalid ui_type: 'foobar'"):
ui_factory.get_ui("foobar")
def testUIFactoryCreatesReadlineUI(self):
ui = ui_factory.get_ui("readline")
self.assertIsInstance(ui, readline_ui.ReadlineUI)
def invoke_node_stepper(self,
node_stepper,
restore_variable_values_on_exit=True):
"""Overrides method in base class to implement interactive node stepper.
Args:
node_stepper: (`stepper.NodeStepper`) The underlying NodeStepper API
object.
restore_variable_values_on_exit: (`bool`) Whether any variables whose
values have been altered during this node-stepper invocation should be
restored to their old values when this invocation ends.
Returns:
The same return values as the `Session.run()` call on the same fetches as
the NodeStepper.
"""
stepper = stepper_cli.NodeStepperCLI(node_stepper)
# On exiting the node-stepper CLI, the finalize method of the node_stepper
# object will be called, ensuring that the state of the graph will be the
# same as if the stepping did not happen.
# TODO(cais): Perhaps some users will want the effect of the interactive
# stepping and value injection to persist. When that happens, make the call
# to finalize optional.
stepper_ui = ui_factory.get_ui(
self._ui_type,
on_ui_exit=(node_stepper.restore_variable_values if
restore_variable_values_on_exit else None))
stepper_ui.register_command_handler(
"list_sorted_nodes",
stepper.list_sorted_nodes,
stepper.arg_parsers["list_sorted_nodes"].format_help(),
prefix_aliases=["lt", "lsn"])
stepper_ui.register_command_handler(
"cont",
stepper.cont,
stepper.arg_parsers["cont"].format_help(),
prefix_aliases=["ct", "c"])
stepper_ui.register_command_handler(
"step",
stepper.step,
stepper.arg_parsers["step"].format_help(),
prefix_aliases=["st", "s"])
stepper_ui.register_command_handler(
"print_tensor",
stepper.print_tensor,
stepper.arg_parsers["print_tensor"].format_help(),
prefix_aliases=["pt"])
stepper_ui.register_command_handler(
"inject_value",
stepper.inject_value,
stepper.arg_parsers["inject_value"].format_help(),
prefix_aliases=["inject", "override_value", "override"])
# Register tab completion candidates.
stepper_ui.register_tab_comp_context([
"cont", "ct", "c", "pt", "inject_value", "inject", "override_value",
"override"
], [str(elem) for elem in node_stepper.sorted_nodes()])
# TODO(cais): Tie up register_tab_comp_context to a single alias to shorten
# calls like this.
return stepper_ui.run_ui(
init_command="lt",
title="Node Stepper: " + self._run_description,
title_color="blue_on_white")
def testUIFactoryRaisesExceptionOnInvalidUIType(self):
with self.assertRaisesRegexp(ValueError, "Invalid ui_type: 'foobar'"):
ui_factory.get_ui("foobar")
def testUIFactoryRaisesExceptionOnInvalidUITypeGivenAvailable(self):
with self.assertRaisesRegexp(ValueError,
"Invalid ui_type: 'readline'"):
ui_factory.get_ui("readline", available_ui_types=["curses"])
