experiments/STT-tensorflow
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Replace tf.estimator.inputs with tf.compat.v1.estimator.inputs

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PiperOrigin-RevId: 223118522
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A. Unique TensorFlower 2018-11-27 23:53:33 -08:00 committed by TensorFlower Gardener
parent 567c0692de
commit 95e808ba44
3 changed files with 7 additions and 10 deletions
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4
tensorflow/examples/learn/iris_custom_decay_dnn.py
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@ -76,12 +76,12 @@ def main(unused_argv):
classifier = tf.estimator.Estimator(model_fn=my_model)
# Train.
train_input_fn = tf.estimator.inputs.numpy_input_fn(
train_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(
x={X_FEATURE: x_train}, y=y_train, num_epochs=None, shuffle=True)
classifier.train(input_fn=train_input_fn, steps=1000)
# Predict.
test_input_fn = tf.estimator.inputs.numpy_input_fn(
test_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(
x={X_FEATURE: x_test}, y=y_test, num_epochs=1, shuffle=False)
predictions = classifier.predict(input_fn=test_input_fn)
y_predicted = np.array(list(p['class'] for p in predictions))

4
tensorflow/examples/learn/iris_custom_model.py
View File

@ -73,12 +73,12 @@ def main(unused_argv):
classifier = tf.estimator.Estimator(model_fn=my_model)
# Train.
train_input_fn = tf.estimator.inputs.numpy_input_fn(
train_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(
x={X_FEATURE: x_train}, y=y_train, num_epochs=None, shuffle=True)
classifier.train(input_fn=train_input_fn, steps=1000)
# Predict.
test_input_fn = tf.estimator.inputs.numpy_input_fn(
test_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(
x={X_FEATURE: x_test}, y=y_test, num_epochs=1, shuffle=False)
predictions = classifier.predict(input_fn=test_input_fn)
y_predicted = np.array(list(p['class'] for p in predictions))

9
tensorflow/examples/tutorials/layers/cnn_mnist.py
View File

@ -134,7 +134,7 @@ def main(unused_argv):
tensors=tensors_to_log, every_n_iter=50)
# Train the model
train_input_fn = tf.estimator.inputs.numpy_input_fn(
train_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(
x={"x": train_data},
y=train_labels,
batch_size=100,
@ -146,11 +146,8 @@ def main(unused_argv):
hooks=[logging_hook])
# Evaluate the model and print results
eval_input_fn = tf.estimator.inputs.numpy_input_fn(
x={"x": eval_data},
y=eval_labels,
num_epochs=1,
shuffle=False)
eval_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(
x={"x": eval_data}, y=eval_labels, num_epochs=1, shuffle=False)
eval_results = mnist_classifier.evaluate(input_fn=eval_input_fn)
print(eval_results)