def _read_latest_config_files(self, run_path_pairs):
"""Reads and returns the projector config files in every run directory."""
configs = {}
config_fpaths = {}
for run_name, logdir in run_path_pairs:
config = ProjectorConfig()
config_fpath = os.path.join(logdir, PROJECTOR_FILENAME)
if file_io.file_exists(config_fpath):
file_content = file_io.read_file_to_string(config_fpath)
text_format.Merge(file_content, config)
has_tensor_files = False
for embedding in config.embeddings:
if embedding.tensor_path:
has_tensor_files = True
break
if not config.model_checkpoint_path:
# See if you can find a checkpoint file in the logdir.
ckpt_path = _find_latest_checkpoint(logdir)
if not ckpt_path and not has_tensor_files:
continue
if ckpt_path:
config.model_checkpoint_path = ckpt_path
# Sanity check for the checkpoint file.
if (config.model_checkpoint_path
and not checkpoint_exists(config.model_checkpoint_path)):
logging.warning('Checkpoint file %s not found',
config.model_checkpoint_path)
continue
configs[run_name] = config
config_fpaths[run_name] = config_fpath
return configs, config_fpaths
def _read_config_files(self, run_paths):
configs = {}
config_fpaths = {}
for run_name, logdir in run_paths.items():
config_fpath = os.path.join(logdir, PROJECTOR_FILENAME)
if not file_io.file_exists(config_fpath):
# Skip runs that have no config file.
continue
# Read the config file.
file_content = file_io.read_file_to_string(config_fpath).decode(
'utf-8')
config = ProjectorConfig()
text_format.Merge(file_content, config)
if not config.model_checkpoint_path:
# See if you can find a checkpoint file in the logdir.
ckpt_path = latest_checkpoint(logdir)
if not ckpt_path:
# Or in the parent of logdir.
ckpt_path = latest_checkpoint(os.path.join('../', logdir))
if not ckpt_path:
logging.warning('Cannot find model checkpoint in %s',
logdir)
continue
config.model_checkpoint_path = ckpt_path
# Sanity check for the checkpoint file.
if not file_io.file_exists(config.model_checkpoint_path):
logging.warning('Checkpoint file %s not found',
config.model_checkpoint_path)
continue
configs[run_name] = config
config_fpaths[run_name] = config_fpath
return configs, config_fpaths
def _read_config_files(self, run_paths):
configs = {}
config_fpaths = {}
for run_name, logdir in run_paths.items():
config_fpath = os.path.join(logdir, PROJECTOR_FILENAME)
if not file_io.file_exists(config_fpath):
# Skip runs that have no config file.
continue
# Read the config file.
file_content = file_io.read_file_to_string(config_fpath).decode('utf-8')
config = ProjectorConfig()
text_format.Merge(file_content, config)
if not config.model_checkpoint_path:
# See if you can find a checkpoint file in the logdir.
ckpt_path = latest_checkpoint(logdir)
if not ckpt_path:
# Or in the parent of logdir.
ckpt_path = latest_checkpoint(os.path.join('../', logdir))
if not ckpt_path:
logging.warning('Cannot find model checkpoint in %s', logdir)
continue
config.model_checkpoint_path = ckpt_path
# Sanity check for the checkpoint file.
if not file_io.file_exists(config.model_checkpoint_path):
logging.warning('Checkpoint file %s not found',
config.model_checkpoint_path)
continue
configs[run_name] = config
config_fpaths[run_name] = config_fpath
return configs, config_fpaths
def _read_latest_config_files(self, run_path_pairs):
"""Reads and returns the projector config files in every run directory."""
configs = {}
config_fpaths = {}
for run_name, logdir in run_path_pairs:
config = ProjectorConfig()
config_fpath = os.path.join(logdir, PROJECTOR_FILENAME)
if file_io.file_exists(config_fpath):
file_content = file_io.read_file_to_string(config_fpath)
text_format.Merge(file_content, config)
has_tensor_files = False
for embedding in config.embeddings:
if embedding.tensor_path:
has_tensor_files = True
break
if not config.model_checkpoint_path:
# See if you can find a checkpoint file in the logdir.
ckpt_path = _find_latest_checkpoint(logdir)
if not ckpt_path and not has_tensor_files:
continue
if ckpt_path:
config.model_checkpoint_path = ckpt_path
# Sanity check for the checkpoint file.
if (config.model_checkpoint_path and
not checkpoint_exists(config.model_checkpoint_path)):
logging.warning('Checkpoint file %s not found',
config.model_checkpoint_path)
continue
configs[run_name] = config
config_fpaths[run_name] = config_fpath
return configs, config_fpaths
def _read_config_files(self, run_paths, logdir):
# If there are no summary event files, the projector can still work,
# thus treating the `logdir` as the model checkpoint directory.
if not run_paths:
run_paths['.'] = logdir
configs = {}
config_fpaths = {}
for run_name, logdir in run_paths.items():
config = ProjectorConfig()
config_fpath = os.path.join(logdir, PROJECTOR_FILENAME)
if file_io.file_exists(config_fpath):
file_content = file_io.read_file_to_string(
config_fpath).decode('utf-8')
text_format.Merge(file_content, config)
has_tensor_files = False
for embedding in config.embeddings:
if embedding.tensor_path:
has_tensor_files = True
break
if not config.model_checkpoint_path:
# See if you can find a checkpoint file in the logdir.
ckpt_path = latest_checkpoint(logdir)
if not ckpt_path:
# Or in the parent of logdir.
ckpt_path = latest_checkpoint(os.path.join('../', logdir))
if not ckpt_path and not has_tensor_files:
logging.warning('Cannot find model checkpoint in %s',
logdir)
continue
if ckpt_path:
config.model_checkpoint_path = ckpt_path
# Sanity check for the checkpoint file.
if (config.model_checkpoint_path
and not checkpoint_exists(config.model_checkpoint_path)):
logging.warning('Checkpoint file %s not found',
config.model_checkpoint_path)
continue
configs[run_name] = config
config_fpaths[run_name] = config_fpath
return configs, config_fpaths
def _read_config_files(self, run_paths, logdir):
# If there are no summary event files, the projector can still work,
# thus treating the `logdir` as the model checkpoint directory.
if not run_paths:
run_paths['.'] = logdir
configs = {}
config_fpaths = {}
for run_name, logdir in run_paths.items():
config = ProjectorConfig()
config_fpath = os.path.join(logdir, PROJECTOR_FILENAME)
if file_io.file_exists(config_fpath):
file_content = file_io.read_file_to_string(config_fpath).decode('utf-8')
text_format.Merge(file_content, config)
has_tensor_files = False
for embedding in config.embeddings:
if embedding.tensor_path:
has_tensor_files = True
break
if not config.model_checkpoint_path:
# See if you can find a checkpoint file in the logdir.
ckpt_path = latest_checkpoint(logdir)
if not ckpt_path:
# Or in the parent of logdir.
ckpt_path = latest_checkpoint(os.path.join('../', logdir))
if not ckpt_path and not has_tensor_files:
logging.warning('Cannot find model checkpoint in %s', logdir)
continue
if ckpt_path:
config.model_checkpoint_path = ckpt_path
# Sanity check for the checkpoint file.
if (config.model_checkpoint_path and
not checkpoint_exists(config.model_checkpoint_path)):
logging.warning('Checkpoint file %s not found',
config.model_checkpoint_path)
continue
configs[run_name] = config
config_fpaths[run_name] = config_fpath
return configs, config_fpaths
