in src/python/tensorflow_cloud/core/containerize.py [0:0]
def _get_file_path_map(self):
"""Maps local file paths to the Docker daemon process location.
Dictionary mapping file paths in the local file system to the paths
in the Docker daemon process location. The `key` or source is the path
of the file that will be used when creating the archive. The `value`
or destination is set as the `arcname` for the file at this time.
When extracting files from the archive, they are extracted to the
destination path.
Returns:
A file path map.
"""
location_map = {}
if self.entry_point is None and sys.argv[0].endswith("py"):
self.entry_point = sys.argv[0]
# Map entry_point directory to the dst directory.
if not self.called_from_notebook or self.entry_point is not None:
entry_point_dir, _ = os.path.split(self.entry_point)
if not entry_point_dir: # Current directory
entry_point_dir = "."
location_map[entry_point_dir] = self.destination_dir
# Place preprocessed_entry_point in the dst directory.
if self.preprocessed_entry_point is not None:
_, preprocessed_entry_point_file_name = os.path.split(
self.preprocessed_entry_point
)
location_map[self.preprocessed_entry_point] = os.path.join(
self.destination_dir, preprocessed_entry_point_file_name
)
# Place requirements_txt in the dst directory.
if self.requirements_txt is not None:
_, requirements_txt_name = os.path.split(self.requirements_txt)
location_map[self.requirements_txt] = os.path.join(
self.destination_dir, requirements_txt_name
)
# Place Docker file in the root directory.
location_map[self.docker_file_path] = "Dockerfile"
return location_map