运行以下语句时,我收到以下错误
b = tf.Variable(tf.zeros([10]))
当我在python中逐行运行代码时,我收到错误
W = tf.Variable(tf.zeros([784,10])) b = tf.Variable(tf.zeros([10]))
追加
self._values.append(self._type_checker.CheckValue(value))
AttributeError: 'float' object has no attribute '_values'
Python 3.7 OSX
这是完整的代码
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
import sys
from tensorflow.examples.tutorials.mnist import input_data
import tensorflow as tf
FLAGS = None
def main(_):
# Import data
mnist = input_data.read_data_sets(FLAGS.data_dir, one_hot=True)
# Create the model
x = tf.placeholder(tf.float32, [None, 784])
W = tf.Variable(tf.zeros([784, 10]))
b = tf.Variable(tf.zeros([10]))
y = tf.matmul(x, W) + b
# Define loss and optimizer
y_ = tf.placeholder(tf.float32, [None, 10])
# The raw formulation of cross-entropy,
#
# tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(tf.nn.softmax(y)),
# reduction_indices=[1]))
#
# can be numerically unstable.
#
# So here we use tf.nn.softmax_cross_entropy_with_logits on the raw
# outputs of 'y', and then average across the batch.
cross_entropy = tf.reduce_mean(
tf.nn.softmax_cross_entropy_with_logits(labels=y_, logits=y))
train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy)
sess = tf.InteractiveSession()
tf.global_variables_initializer().run()
# Train
for _ in range(1000):`enter code here`
batch_xs, batch_ys = mnist.train.next_batch(100)
sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys})
# Test trained model
correct_prediction = tf.equal(tf.argmax(y, 1), tf.argmax(y_, 1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
print(sess.run(accuracy, feed_dict={x: mnist.test.images,
y_: mnist.test.labels}))
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--data_dir', type=str, default='/tmp/tensorflow/mnist/input_data',
help='Directory for storing input data')
FLAGS, unparsed = parser.parse_known_args()
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
运行整个文件时完成错误日志
/Users/av/tensorflow/lib/python3.7/importlib/_bootstrap.py:219: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.7
return f(*args, **kwds)
Extracting /tmp/tensorflow/mnist/input_data/train-images-idx3-ubyte.gz
Extracting /tmp/tensorflow/mnist/input_data/train-labels-idx1-ubyte.gz
Extracting /tmp/tensorflow/mnist/input_data/t10k-images-idx3-ubyte.gz
Extracting /tmp/tensorflow/mnist/input_data/t10k-labels-idx1-ubyte.gz
Traceback (most recent call last):
File "mnist.py", line 79, in <module>
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
File "/Users/av/tensorflow/lib/python3.7/site-packages/tensorflow/python/platform/app.py", line 48, in run
_sys.exit(main(_sys.argv[:1] + flags_passthrough))
File "mnist.py", line 41, in main
W = tf.Variable(tf.zeros([784, 10]))
File "/Users/av/tensorflow/lib/python3.7/site-packages/tensorflow/python/ops/array_ops.py", line 1439, in zeros
output = constant(zero, shape=shape, dtype=dtype, name=name)
File "/Users/av/tensorflow/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py", line 208, in constant
value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "/Users/av/tensorflow/lib/python3.7/site-packages/tensorflow/python/framework/tensor_util.py", line 483, in make_tensor_proto
append_fn(tensor_proto, proto_values)
SystemError: <built-in function AppendFloat32ArrayToTensorProto> returned NULL without setting an error
应该怎样解决这个问题?