Tensorflow - 'Unable to get element as bytes' error
以下代码：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 | import numpy as np import tensorflow as tf from sklearn.model_selection import train_test_split import pandas as pd # DATA PREPARE df = pd.read_csv('housing.csv') df = df.dropna() print(df.head) print(df.describe()) print(df.info()) # NORMALIZATION from sklearn.preprocessing import MinMaxScaler scaler = MinMaxScaler() scaler.fit(df[['housing_median_age', 'total_rooms', 'total_bedrooms', 'population', 'households', 'median_income', 'median_house_value']]) df_scaled_cols = scaler.transform(df[['housing_median_age', 'total_rooms', 'total_bedrooms', 'population', 'households', 'median_income', 'median_house_value']]) df_scaled_cols = pd.DataFrame(data=df_scaled_cols, columns=['housing_median_age', 'total_rooms', 'total_bedrooms', 'population', 'households', 'median_income', 'median_house_value']) df = pd.concat([df_scaled_cols, df['ocean_proximity']], axis=1) # DATAFRAME INTO X AND Y -> TRAIN TEST SPLIT x_data = df[['housing_median_age', 'total_rooms', 'total_bedrooms', 'population', 'households', 'median_income', 'ocean_proximity']] y_label = df['median_house_value'] X_train, X_test, y_train, y_test = train_test_split(x_data, y_label, test_size=0.3) # FEATURE COLUMNS FROM DATA m_age = tf.feature_column.numeric_column('housing_median_age') rooms = tf.feature_column.numeric_column('total_rooms') bedrooms = tf.feature_column.numeric_column('total_bedrooms') population = tf.feature_column.numeric_column('population') households = tf.feature_column.numeric_column('households') income = tf.feature_column.numeric_column('median_income') ocean = tf.feature_column.categorical_column_with_hash_bucket('ocean_proximity', hash_bucket_size=10) embedded_ocean = tf.feature_column.embedding_column(ocean, dimension=4) feat_cols = [m_age, rooms, bedrooms, population, households, income, embedded_ocean] # 3 INPUT FUNCTIONS train_input_func = tf.estimator.inputs.pandas_input_fn(x=X_train, y=y_train, batch_size=10, num_epochs=1000, shuffle=True) test_input_func = tf.estimator.inputs.pandas_input_fn(x=X_test, y=y_test, batch_size=10, num_epochs=1, shuffle=False) predict_input_func = tf.estimator.inputs.pandas_input_fn(x=X_test, batch_size=10, num_epochs=1, shuffle=False) # DNN_Reg MODEL dnn_model = tf.estimator.DNNRegressor(hidden_units=[10,10,10], feature_columns=feat_cols) dnn_model.train(input_fn=train_input_func, steps=1000) |
导致错误：
Traceback (most recent call last): File
"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py",
line 1278, in _do_call
return fn(*args) File"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py",
line 1263, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata) File"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py",
line 1350, in _call_tf_sessionrun
run_metadata) tensorflow.python.framework.errors_impl.InternalError: Unable to get
element as bytes.During handling of the above exception, another exception occurred:
Traceback (most recent call last): File
"C:/Users/Admin/Documents/PycharmProjects/TF_Regression_Project/project.py",
line 69, in
dnn_model.train(input_fn=train_input_func, steps=1000) File"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\estimator\estimator.py",
line 376, in train
loss = self._train_model(input_fn, hooks, saving_listeners) File"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\estimator\estimator.py",
line 1145, in _train_model
return self._train_model_default(input_fn, hooks, saving_listeners) File
"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\estimator\estimator.py",
line 1173, in _train_model_default
saving_listeners) File"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\estimator\estimator.py",
line 1451, in _train_with_estimator_spec
_, loss = mon_sess.run([estimator_spec.train_op, estimator_spec.loss]) File
"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\training\monitored_session.py",
line 695, in exit
self._close_internal(exception_type) File"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\training\monitored_session.py",
line 732, in _close_internal
self._sess.close() File"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\training\monitored_session.py",
line 980, in close
self._sess.close() File"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\training\monitored_session.py",
line 1124, in close
ignore_live_threads=True) File"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\training\coordinator.py",
line 389, in join
six.reraise(*self._exc_info_to_raise) File"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\six.py",
line 692, in reraise
raise value.with_traceback(tb) File"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\estimator\inputs\queues\feeding_queue_runner.py",
line 94, in _run
sess.run(enqueue_op, feed_dict=feed_dict) File"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py",
line 877, in run
run_metadata_ptr) File"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py",
line 1100, in _run
feed_dict_tensor, options, run_metadata) File"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py",
line 1272, in _do_run
run_metadata) File"C:\Users\Admin\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py",
line 1291, in _do_call
raise type(e)(node_def, op, message) tensorflow.python.framework.errors_impl.InternalError: Unable to get
element as bytes.
里面出了什么问题？
问题在于规范化。
我没有使用sklearn方法，而是执行了以下操作：
1 2 3 | df[['housing_median_age', 'total_rooms', 'total_bedrooms', 'population', 'households', 'median_income', 'median_house_value']] = df[['housing_median_age', 'total_rooms', 'total_bedrooms', 'population', 'households', 'median_income', 'median_house_value']].apply(lambda x: (x-x.min()) / (x.max()-x.min())) |
因此，总而言之，我做了与sklearn相同的事情，但手动 - 使用lambda。