Python

I want to pickle the history object after running a keras fit on tensorflow. But I am getting an error.

import gzip
import numpy as np
import os
import pickle
import tensorflow as tf
from tensorflow import keras


with gzip.open('mnist.pkl.gz', 'rb') as f:
    train_set, test_set = pickle.load(f, encoding='latin1')

X_train = np.asarray(train_set[0])
y_train = np.asarray(train_set[1])

X_test = np.asarray(test_set[0])
y_test = np.asarray(test_set[1])

X_valid, X_train = X_train[:5000]/255.0, X_train[5000:]/255.0
y_valid, y_train = y_train[:5000], y_train[5000:]

class_names = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat',
               'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle Boot']

model = keras.models.Sequential()
model.add(keras.layers.Flatten(input_shape=[28,28]))
model.add(keras.layers.Dense(300, activation = 'relu'))
model.add(keras.layers.Dense(100, activation = 'relu'))
model.add(keras.layers.Dense(10, activation = 'softmax'))
model.summary()

model.compile(loss='sparse_categorical_crossentropy',
              optimizer='sgd',
              metrics=['accuracy'])

history = model.fit(X_train, y_train, epochs=1,
                    validation_data =(X_valid, y_valid))

if not os.path.isdir('models'):
    os.mkdir('models')

model.save('models/basic.h5')
with open('models/basic_history.pickle', 'wb') as f:
    pickle.dump(history, f)

It gives me the following error:

Traceback (most recent call last):
  File "main.py", line 69, in <module>
    pickle.dump(history, f)
TypeError: can't pickle _thread._local objects

PS: To get the code to run, download the fashion_mnist data: https://s3.amazonaws.com/img-datasets/mnist.pkl.g

Answer

As Karl suggested, the history object cannot be pickled. But it’s dictionary can:

with open('models/basic_history.pickle', 'wb') as f:
    pickle.dump(history.history, f)

Cannot pickle Tensorflow object in Python – TypeError: can’t pickle _thread._local objects

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Answer