# Path: nlp/model/amplmodel.py
# class QNAmplModel(QuasiNewtonModel, AmplModel):
#     """AMPL model with quasi-Newton Hessian approximation."""
#     pass  # All the work is done by the parent classes.
# 
# Path: nlp/tools/logs.py
# def config_logger(name, format='%(message)s', datefmt=None,
#                   stream=sys.stdout, level=logging.INFO,
#                   filename=None, filemode='w', filelevel=None,
#                   propagate=False):
#     """Basic configuration for the logging system.
# 
#      Similar to logging.basicConfig but the logger `name` is configurable and
#      both a file output and a stream output can be created. Returns a logger
#      object.
# 
#     The default behaviour is to create a StreamHandler which writes to
#     sys.stdout, set a formatter using the format string, and add the handler to
#     the `name` logger.
# 
#     :parameters:
# 
#         :name:      Logger name
#         :format:    handler format string (default=``%(message)s``)
#         :datefmt:   handler date/time format specifier
#         :stream:    initialize the StreamHandler using ``stream``
#                     (None disables the stream, default=``sys.stdout``)
#         :level:     logger level (default=``INFO``).
#         :filename:  create FileHandler using ``filename`` (default=``None``)
#         :filemode:  open ``filename`` with specified filemode (``w`` or ``a``)
#         :filelevel: logger level for file logger (default=``level``)
#         :propagate: propagate message to parent (default=``False``)
#     """
#     # Get a logger for the specified name
#     logger = logging.getLogger(name)
#     logger.setLevel(level)
#     logger.propagate = propagate
# 
#     # Remove existing handlers, otherwise multiple handlers can accrue
#     for hdlr in logger.handlers:
#         logger.removeHandler(hdlr)
# 
#     # Add handlers. Add NullHandler if no file or stream output so that
#     # modules don't emit a warning about no handler.
#     if not (filename or stream):
#         logger.addHandler(logging.NullHandler())
# 
#     if filename:
#         hdlr = logging.FileHandler(filename, filemode)
#         if filelevel is None:
#             filelevel = level
#             hdlr.setLevel(filelevel)
# 
#     if stream:
#         hdlr = logging.StreamHandler(stream)
#         hdlr.setLevel(level)
# 
#     hdlr.setFormatter(logging.Formatter(format))
#     logger.addHandler(hdlr)
# 
#     return logger


import logging
import sys
from argparse import ArgumentParser
from nlp.model.amplmodel import QNAmplModel
from nlp.tools.logs import config_logger
from pykrylov.linop import InverseLBFGSOperator
    from nlp.optimize.lbfgs import LBFGS
    from nlp.optimize.lbfgs import WolfeLBFGS as LBFGS
        ts = -1.0 if lbfgs.tsolve is None else -lbfgs.tsolve
    return (it, fc, gc, gn, ts)

desc = """Linesearch-based limited-memory BFGS method in inverse form."""

# Define allowed command-line options.
parser = ArgumentParser(description=desc)
parser.add_argument("-p", "--pairs", type=int,
                    default=5, dest="npairs", help="BFGS memory")
parser.add_argument("-a", "--armijo", action="store_true", dest="armijo",
                    default=False, help="use improved Armijo linesearch")
parser.add_argument("-i", "--iter", type=int,
                    default=100, dest="maxiter",
                    help="maximum number of iterations")

# Parse command-line arguments.
(args, other) = parser.parse_known_args()

if args.armijo:
else:

nprobs = len(other)
if nprobs == 0:
    raise ValueError("Please supply problem name as argument")

# Create root logger.
logger = config_logger("nlp",
                       "%(name)-3s %(levelname)-5s %(message)s")

# Create LBFGS logger.

# Path: nlp/model/amplmodel.py
# class QNAmplModel(QuasiNewtonModel, AmplModel):
#     """AMPL model with quasi-Newton Hessian approximation."""
#     pass  # All the work is done by the parent classes.
# 
# Path: nlp/tools/logs.py
# def config_logger(name, format='%(message)s', datefmt=None,
#                   stream=sys.stdout, level=logging.INFO,
#                   filename=None, filemode='w', filelevel=None,
#                   propagate=False):
#     """Basic configuration for the logging system.
# 
#      Similar to logging.basicConfig but the logger `name` is configurable and
#      both a file output and a stream output can be created. Returns a logger
#      object.
# 
#     The default behaviour is to create a StreamHandler which writes to
#     sys.stdout, set a formatter using the format string, and add the handler to
#     the `name` logger.
# 
#     :parameters:
# 
#         :name:      Logger name
#         :format:    handler format string (default=``%(message)s``)
#         :datefmt:   handler date/time format specifier
#         :stream:    initialize the StreamHandler using ``stream``
#                     (None disables the stream, default=``sys.stdout``)
#         :level:     logger level (default=``INFO``).
#         :filename:  create FileHandler using ``filename`` (default=``None``)
#         :filemode:  open ``filename`` with specified filemode (``w`` or ``a``)
#         :filelevel: logger level for file logger (default=``level``)
#         :propagate: propagate message to parent (default=``False``)
#     """
#     # Get a logger for the specified name
#     logger = logging.getLogger(name)
#     logger.setLevel(level)
#     logger.propagate = propagate
# 
#     # Remove existing handlers, otherwise multiple handlers can accrue
#     for hdlr in logger.handlers:
#         logger.removeHandler(hdlr)
# 
#     # Add handlers. Add NullHandler if no file or stream output so that
#     # modules don't emit a warning about no handler.
#     if not (filename or stream):
#         logger.addHandler(logging.NullHandler())
# 
#     if filename:
#         hdlr = logging.FileHandler(filename, filemode)
#         if filelevel is None:
#             filelevel = level
#             hdlr.setLevel(filelevel)
# 
#     if stream:
#         hdlr = logging.StreamHandler(stream)
#         hdlr.setLevel(level)
# 
#     hdlr.setFormatter(logging.Formatter(format))
#     logger.addHandler(hdlr)
# 
#     return logger


# Path: nlp/drivers/nlp_lbfgs.py
import logging
import sys
from argparse import ArgumentParser
from nlp.model.amplmodel import QNAmplModel
from nlp.tools.logs import config_logger
from pykrylov.linop import InverseLBFGSOperator
    from nlp.optimize.lbfgs import LBFGS
    from nlp.optimize.lbfgs import WolfeLBFGS as LBFGS

        ts = -1.0 if lbfgs.tsolve is None else -lbfgs.tsolve
    return (it, fc, gc, gn, ts)

desc = """Linesearch-based limited-memory BFGS method in inverse form."""

# Define allowed command-line options.
parser = ArgumentParser(description=desc)
parser.add_argument("-p", "--pairs", type=int,
                    default=5, dest="npairs", help="BFGS memory")
parser.add_argument("-a", "--armijo", action="store_true", dest="armijo",
                    default=False, help="use improved Armijo linesearch")
parser.add_argument("-i", "--iter", type=int,
                    default=100, dest="maxiter",
                    help="maximum number of iterations")

# Parse command-line arguments.
(args, other) = parser.parse_known_args()

if args.armijo:
else:

nprobs = len(other)
if nprobs == 0:
    raise ValueError("Please supply problem name as argument")

# Create root logger.
logger = config_logger("nlp",
                       "%(name)-3s %(levelname)-5s %(message)s")

# Create LBFGS logger.

slv_log = config_logger("nlp.lbfgs",