# Copyright 2022 Cerebras Systems.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import shutil
from typing import Optional
import yaml
[docs]def check_and_create_output_dirs(output_dir, filetype):
contains_filetype = False
if os.path.isdir(output_dir):
for fname in os.listdir(output_dir):
if filetype in fname:
contains_filetype = True
break
if contains_filetype:
_in = input(
f"Output directory already contains {filetype} file(s)."
+ " Do you want to delete the folder to write"
+ " new records in the same output folder name? (yes/no): "
)
if _in.lower() in ["y", "yes"]:
shutil.rmtree(output_dir)
elif _in.lower() in ["n", "no"]:
raise IsADirectoryError(
"Create a new folder for the files you want to write!!"
)
else:
raise ValueError(f"Inputs can be yes, no, y or n. Received {_in}!!")
os.makedirs(output_dir, exist_ok=True)
[docs]def save_params(params, model_dir, fname="params.yaml"):
"""
Writes and saves a dictionary to a file in the model_dir.
:param dict params: dict we want to write to a file in model_dir
:param string model_dir: Directory we want to write to
:param string fname: Name of file in model_dir we want to save to.
"""
if not model_dir:
raise ValueError(
"model_dir is not provided. For saving params, user-defined"
+ " model_dir must be passed either through the command line"
+ " or from the yaml"
)
params_fname = os.path.join(model_dir, fname,)
try:
os.makedirs(os.path.dirname(params_fname), exist_ok=True)
except OSError as error:
raise ValueError(
f"Invalid path {model_dir} provided. Check the model_dir path!"
)
with open(params_fname, "w+") as _fout:
yaml.dump(params, _fout, default_flow_style=False)
[docs]def update_debug_args_with_mem_limits(
debug_args: 'DebugArgs', runconfig: Optional[dict] = None
):
"""Update debug args with runconfig memory limits"""
if not runconfig:
return
prop_to_pb_attr = {
"compile_crd_memory_gi": debug_args.debug_usr.compile_coord_resource,
"execute_crd_memory_gi": debug_args.debug_usr.execute_coord_resource,
"wrk_memory_gi": debug_args.debug_usr.worker_resource,
"act_memory_gi": debug_args.debug_usr.activation_resource,
"cmd_memory_gi": debug_args.debug_usr.command_resource,
"wgt_memory_gi": debug_args.debug_usr.weight_resource,
}
for prop, pb_attr in prop_to_pb_attr.items():
if prop in runconfig:
pb_attr.memory_bytes = runconfig[prop] << 30 # gi to bytes