I followed these two posts to understand about restoring a saved model and then extracting variables from it:
- Extracting weights values from a tensorflow model checkpoint
- How to examine the feature weights of a Tensorflow LinearClassifier?
But now I am unable to understand as to what do those variables mean exactly and how to understand the relative importance given by the model to the features in the learning process? Below is the output of tf.train.list_variables and tf.train.load_variables (respectively) from my code:
>> tf.train.list_variables('./dnn_fe_trial1/model.ckpt-1')
[('dnn/hiddenlayer_0/biases', [50]),
('dnn/hiddenlayer_0/biases/enlayer_0/biases/part_0/Adam', [50]),
('dnn/hiddenlayer_0/biases/enlayer_0/biases/part_0/Adam_1', [50]),
('dnn/hiddenlayer_0/weights', [61, 50]),
('dnn/hiddenlayer_0/weights/nlayer_0/weights/part_0/Adam', [61, 50]),
('dnn/hiddenlayer_0/weights/nlayer_0/weights/part_0/Adam_1', [61, 50]),
('dnn/input_from_feature_columns/brand_embedding/weights', [10000, 16]),
('dnn/input_from_feature_columns/brand_embedding/weights/mbedding/weights/part_0/Adam', [10000, 16]),
('dnn/input_from_feature_columns/brand_embedding/weights/mbedding/weights/part_0/Adam_1', [10000, 16]),
('dnn/input_from_feature_columns/city_embedding/weights', [12, 3]),
('dnn/input_from_feature_columns/city_embedding/weights/mbedding/weights/part_0/Adam', [12, 3]),
('dnn/input_from_feature_columns/city_embedding/weights/mbedding/weights/part_0/Adam_1', [12, 3]),
('dnn/input_from_feature_columns/dow_embedding/weights', [7, 3]),
('dnn/input_from_feature_columns/dow_embedding/weights/mbedding/weights/part_0/Adam', [7, 3]),
('dnn/input_from_feature_columns/dow_embedding/weights/mbedding/weights/part_0/Adam_1', [7, 3]),
('dnn/input_from_feature_columns/l_cat_embedding/weights', [11, 3]),
('dnn/input_from_feature_columns/l_cat_embedding/weights/mbedding/weights/part_0/Adam', [11, 3]),
('dnn/input_from_feature_columns/l_cat_embedding/weights/mbedding/weights/part_0/Adam_1', [11, 3]),
('dnn/input_from_feature_columns/product_id_embedding/weights', [10000, 16]),
('dnn/input_from_feature_columns/product_id_embedding/weights/mbedding/weights/part_0/Adam', [10000, 16]),
('dnn/input_from_feature_columns/product_id_embedding/weights/mbedding/weights/part_0/Adam_1', [10000, 16]),
('dnn/input_from_feature_columns/type_id_embedding/weights', [10000, 16]),
('dnn/input_from_feature_columns/type_id_embedding/weights/mbedding/weights/part_0/Adam', [10000, 16]),
('dnn/input_from_feature_columns/type_id_embedding/weights/mbedding/weights/part_0/Adam_1', [10000, 16]),
('dnn/logits/biases', [1]),
('dnn/logits/biases/nn/logits/biases/part_0/Adam', [1]),
('dnn/logits/biases/nn/logits/biases/part_0/Adam_1', [1]),
('dnn/logits/weights', [50, 1]),
('dnn/logits/weights/n/logits/weights/part_0/Adam', [50, 1]),
('dnn/logits/weights/n/logits/weights/part_0/Adam_1', [50, 1]),
('dnn/regression_head/dnn/learning_rate', []),
('dnn/regression_head/train_op/dnn/beta1_power', []),
('dnn/regression_head/train_op/dnn/beta2_power', []),
('global_step', [])]
>> tf.train.load_variable('./dnn_fe_trial1/model.ckpt-1','dnn/hiddenlayer_0/weights')
array([[ 0.14350541, 0.18532775, -0.03176343, ..., -0.07279533,
-0.08580479, -0.07619692],
[ 0.16894072, -0.10593006, 0.06088932, ..., -0.01411209,
-0.26995516, 0.15667924],
[-0.10020741, -0.03164399, -0.14427225, ..., -0.02787848,
-0.15646952, -0.1361219 ],
...,
[ 0.15014522, 0.15378515, -0.05414914, ..., -0.16788298,
-0.14711154, -0.226382 ],
[-0.16823539, 0.2009476 , -0.271177 , ..., -0.10694946,
-0.22870012, -0.13458726],
[-0.13175508, 0.15535942, -0.18468232, ..., -0.1362714 ,
-0.27476427, -0.21606216]], dtype=float32)
