DeepLearningExamples/TensorFlow2/Recommendation/DLRM_and_DCNv2/nn/nn_utils.py

# Copyright (c) 2021, 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.
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# author: Tomasz Grel ([email protected])

from collections import OrderedDict


def create_inputs_dict(numerical_features, categorical_features):
    # Passing inputs as (numerical_features, categorical_features) changes the model
    # input signature to (<tensor, [list of tensors]>).
    # This leads to errors while loading the saved model.
    # TF flattens the inputs while loading the model,
    # so the inputs are converted from (<tensor, [list of tensors]>) -> [list of tensors]
    # see _set_inputs function in training_v1.py:
    # https://github.com/tensorflow/tensorflow/blob/7628750678786f1b65e8905fb9406d8fbffef0db/tensorflow/python/keras/engine/training_v1.py#L2588)
    inputs = OrderedDict()
    inputs['numerical_features'] = numerical_features
    inputs['categorical_features'] = categorical_features
    return inputs