add DeepMimic helper utils
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128
examples/pybullet/gym/pybullet_utils/logger.py
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128
examples/pybullet/gym/pybullet_utils/logger.py
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import pybullet_utils.mpi_util as MPIUtil
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"""
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Some simple logging functionality, inspired by rllab's logging.
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Assumes that each diagnostic gets logged each iteration
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Call logz.configure_output_file() to start logging to a
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tab-separated-values file (some_file_name.txt)
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To load the learning curves, you can do, for example
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A = np.genfromtxt('/tmp/expt_1468984536/log.txt',delimiter='\t',dtype=None, names=True)
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A['EpRewMean']
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"""
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import os.path as osp, shutil, time, atexit, os, subprocess
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class Logger:
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def print2(str):
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if (MPIUtil.is_root_proc()):
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print(str)
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return
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def __init__(self):
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self.output_file = None
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self.first_row = True
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self.log_headers = []
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self.log_current_row = {}
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self._dump_str_template = ""
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return
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def reset(self):
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self.first_row = True
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self.log_headers = []
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self.log_current_row = {}
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if self.output_file is not None:
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self.output_file = open(output_path, 'w')
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return
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def configure_output_file(self, filename=None):
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"""
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Set output directory to d, or to /tmp/somerandomnumber if d is None
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"""
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self.first_row = True
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self.log_headers = []
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self.log_current_row = {}
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output_path = filename or "output/log_%i.txt"%int(time.time())
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out_dir = os.path.dirname(output_path)
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if not os.path.exists(out_dir) and MPIUtil.is_root_proc():
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os.makedirs(out_dir)
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if (MPIUtil.is_root_proc()):
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self.output_file = open(output_path, 'w')
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assert osp.exists(output_path)
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atexit.register(self.output_file.close)
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Logger.print2("Logging data to " + self.output_file.name)
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return
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def log_tabular(self, key, val):
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"""
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Log a value of some diagnostic
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Call this once for each diagnostic quantity, each iteration
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"""
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if self.first_row and key not in self.log_headers:
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self.log_headers.append(key)
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else:
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assert key in self.log_headers, "Trying to introduce a new key %s that you didn't include in the first iteration"%key
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self.log_current_row[key] = val
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return
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def get_num_keys(self):
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return len(self.log_headers)
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def print_tabular(self):
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"""
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Print all of the diagnostics from the current iteration
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"""
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if (MPIUtil.is_root_proc()):
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vals = []
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Logger.print2("-"*37)
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for key in self.log_headers:
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val = self.log_current_row.get(key, "")
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if isinstance(val, float):
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valstr = "%8.3g"%val
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elif isinstance(val, int):
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valstr = str(val)
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else:
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valstr = val
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Logger.print2("| %15s | %15s |"%(key, valstr))
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vals.append(val)
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Logger.print2("-" * 37)
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return
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def dump_tabular(self):
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"""
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Write all of the diagnostics from the current iteration
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"""
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if (MPIUtil.is_root_proc()):
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if (self.first_row):
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self._dump_str_template = self._build_str_template()
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vals = []
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for key in self.log_headers:
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val = self.log_current_row.get(key, "")
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vals.append(val)
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if self.output_file is not None:
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if self.first_row:
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header_str = self._dump_str_template.format(*self.log_headers)
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self.output_file.write(header_str + "\n")
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val_str = self._dump_str_template.format(*map(str,vals))
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self.output_file.write(val_str + "\n")
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self.output_file.flush()
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self.log_current_row.clear()
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self.first_row=False
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return
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def _build_str_template(self):
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num_keys = self.get_num_keys()
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template = "{:<25}" * num_keys
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return template
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