# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
#
# 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.
SPECIAL_KEY = "_nvf_"
[docs]def flat_layer_weights_dict(data: dict):
"""Flattens layer weights dict."""
result = {}
for layer_name, weights in data.items():
if len(weights) != 0:
# If the original layer get_weights return: {"layer0": [array1, array2]}
# We will convert it to: {"layer0_nvf_0": array1, "layer0_nvf_1": array2}
for i, item in enumerate(weights):
result[f"{layer_name}{SPECIAL_KEY}{i}"] = item
return result
[docs]def unflat_layer_weights_dict(data: dict):
"""Unflattens layer weights dict."""
result = {}
for k, v in data.items():
if SPECIAL_KEY in k:
# If the weight is: {"layer0_nvf_0": array1, "layer0_nvf_1": array2}
# We will convert it back to: {"layer0": [array1, array2]} and load it back
layer_name, _ = k.split(SPECIAL_KEY)
if layer_name not in result:
result[layer_name] = []
result[layer_name].append(v)
return result