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# All rights reserved.
#
# SPDX-License-Identifier: BSD-3-Clause
import enum
import importlib
import os
from collections.abc import Callable
import rich.console
import rich.table
from common import ROOT_DIR
from generator import generate, get_algorithms_per_rl_library
from InquirerPy import inquirer, separator
class CLIHandler:
"""CLI handler for the Isaac Lab template."""
def __init__(self):
self.console = rich.console.Console()
@staticmethod
def get_choices(choices: list[str], default: list[str]) -> list[str]:
return default if "all" in choices or "both" in choices else choices
def output_table(self, table: rich.table.Table, new_line_start: bool = True) -> None:
"""Print a rich table to the console.
Args:
table: The table to print.
new_line_start: Whether to print a new line before the table.
"""
self.console.print(table, new_line_start=new_line_start)
def input_select(
self, message: str, choices: list[str], default: str | None = None, long_instruction: str = ""
) -> str:
"""Prompt the user to select an option from a list of choices.
Args:
message: The message to display to the user.
choices: The list of choices to display to the user.
default: The default choice.
long_instruction: The long instruction to display to the user.
Returns:
str: The selected choice.
"""
return inquirer.select(
message=message,
choices=choices,
cycle=True,
default=default,
style=None,
wrap_lines=True,
long_instruction=long_instruction,
).execute()
def input_checkbox(self, message: str, choices: list[str], default: str | None = None) -> list[str]:
"""Prompt the user to select one or more options from a list of choices.
Args:
message: The message to display to the user.
choices: The list of choices to display to the user.
default: The default choice.
Returns:
The selected choices.
"""
def transformer(result: list[str]) -> str:
if "all" in result or "both" in result:
token = "all" if "all" in result else "both"
return f"{token} ({', '.join(choices[: choices.index('---')])})"
return ", ".join(result)
return inquirer.checkbox(
message=message,
choices=[separator.Separator() if "---" in item else item for item in choices],
cycle=True,
default=default,
style=None,
wrap_lines=True,
validate=lambda result: len(result) >= 1,
invalid_message="No option selected (SPACE: select/deselect an option, ENTER: confirm selection)",
transformer=transformer,
).execute()
def input_path(
self,
message: str,
default: str | None = None,
validate: Callable[[str], bool] | None = None,
invalid_message: str = "",
) -> str:
"""Prompt the user to input a path.
Args:
message: The message to display to the user.
default: The default path.
validate: A callable to validate the path.
invalid_message: The message to display to the user if the path is invalid.
Returns:
The input path.
"""
return inquirer.filepath(
message=message,
default=default if default is not None else "",
validate=validate,
invalid_message=invalid_message,
).execute()
def input_text(
self,
message: str,
default: str | None = None,
validate: Callable[[str], bool] | None = None,
invalid_message: str = "",
) -> str:
"""Prompt the user to input a text.
Args:
message: The message to display to the user.
default: The default text.
validate: A callable to validate the text.
invalid_message: The message to display to the user if the text is invalid.
Returns:
The input text.
"""
return inquirer.text(
message=message,
default=default if default is not None else "",
validate=validate,
invalid_message=invalid_message,
).execute()
class State(str, enum.Enum):
Yes = "[green]yes[/green]"
No = "[red]no[/red]"
def main() -> None:
"""Main function to run template generation from CLI."""
cli_handler = CLIHandler()
lab_module = importlib.import_module("isaaclab")
lab_path = os.path.realpath(getattr(lab_module, "__file__", "") or (getattr(lab_module, "__path__", [""])[0]))
is_lab_pip_installed = ("site-packages" in lab_path) or ("dist-packages" in lab_path)
if not is_lab_pip_installed:
# project type
is_external_project = (
cli_handler.input_select(
"Task type:",
choices=["External", "Internal"],
long_instruction=(
"External (recommended): task/project is in its own folder/repo outside the Isaac Lab project.\n"
"Internal: the task is implemented within the Isaac Lab project (in source/isaaclab_tasks)."
),
).lower()
== "external"
)
else:
is_external_project = True
# project path (if 'external')
project_path = None
if is_external_project:
project_path = cli_handler.input_path(
"Project path:",
default=os.path.dirname(ROOT_DIR) + os.sep,
validate=lambda path: not os.path.abspath(path).startswith(os.path.abspath(ROOT_DIR)),
invalid_message="External project path cannot be within the Isaac Lab project",
)
# project/task name
project_name = cli_handler.input_text(
"Project name:" if is_external_project else "Task's folder name:",
validate=lambda name: name.isidentifier(),
invalid_message=(
"Project/task name must be a valid identifier (Letters, numbers and underscores only. No spaces, etc.)"
),
)
# Isaac Lab workflow
# - show supported workflows and features
workflow_table = rich.table.Table(title="RL environment features support according to Isaac Lab workflows")
workflow_table.add_column("Environment feature", no_wrap=True)
workflow_table.add_column("Direct", justify="center")
workflow_table.add_column("Manager-based", justify="center")
workflow_table.add_row("Single-agent", State.Yes, State.Yes)
workflow_table.add_row("Multi-agent", State.Yes, State.No)
workflow_table.add_row("Fundamental/composite spaces (apart from 'Box')", State.Yes, State.No)
cli_handler.output_table(workflow_table)
# - prompt for workflows
supported_workflows = ["Direct | single-agent", "Direct | multi-agent", "Manager-based | single-agent"]
workflow = cli_handler.get_choices(
cli_handler.input_checkbox("Isaac Lab workflow:", choices=[*supported_workflows, "---", "all"]),
default=supported_workflows,
)
workflow = [{"name": item.split(" | ")[0].lower(), "type": item.split(" | ")[1].lower()} for item in workflow]
single_agent_workflow = [item for item in workflow if item["type"] == "single-agent"]
multi_agent_workflow = [item for item in workflow if item["type"] == "multi-agent"]
# RL library
rl_library_algorithms = []
algorithms_per_rl_library = get_algorithms_per_rl_library()
# - show supported RL libraries and features
rl_library_table = rich.table.Table(title="Supported RL libraries")
rl_library_table.add_column("RL/training feature", no_wrap=True)
rl_library_table.add_column("rl_games")
rl_library_table.add_column("rsl_rl")
rl_library_table.add_column("skrl")
rl_library_table.add_column("sb3")
rl_library_table.add_row("ML frameworks", "PyTorch", "PyTorch", "PyTorch, JAX", "PyTorch")
rl_library_table.add_row("Relative performance", "~1X", "~1X", "~1X", "~0.03X")
rl_library_table.add_row(
"Algorithms",
", ".join(algorithms_per_rl_library.get("rl_games", [])),
", ".join(algorithms_per_rl_library.get("rsl_rl", [])),
", ".join(algorithms_per_rl_library.get("skrl", [])),
", ".join(algorithms_per_rl_library.get("sb3", [])),
)
rl_library_table.add_row("Multi-agent support", State.No, State.No, State.Yes, State.No)
rl_library_table.add_row("Distributed training", State.Yes, State.No, State.Yes, State.No)
rl_library_table.add_row("Vectorized training", State.Yes, State.Yes, State.Yes, State.No)
rl_library_table.add_row("Fundamental/composite spaces", State.No, State.No, State.Yes, State.No)
cli_handler.output_table(rl_library_table)
# - prompt for RL libraries
supported_rl_libraries = ["rl_games", "rsl_rl", "skrl", "sb3"] if len(single_agent_workflow) else ["skrl"]
selected_rl_libraries = cli_handler.get_choices(
cli_handler.input_checkbox("RL library:", choices=[*supported_rl_libraries, "---", "all"]),
default=supported_rl_libraries,
)
# - prompt for algorithms per RL library
algorithms_per_rl_library = get_algorithms_per_rl_library(len(single_agent_workflow), len(multi_agent_workflow))
for rl_library in selected_rl_libraries:
algorithms = algorithms_per_rl_library.get(rl_library, [])
if len(algorithms) > 1:
algorithms = cli_handler.get_choices(
cli_handler.input_checkbox(f"RL algorithms for {rl_library}:", choices=[*algorithms, "---", "all"]),
default=algorithms,
)
rl_library_algorithms.append({"name": rl_library, "algorithms": [item.lower() for item in algorithms]})
specification = {
"external": is_external_project,
"path": project_path,
"name": project_name,
"workflows": workflow,
"rl_libraries": rl_library_algorithms,
}
generate(specification)
if __name__ == "__main__":
main()
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