但我是初学者，我不明白帖子中的答案。
我有这段代码
batch_size = 128
num_RELU =1024
graph1 = tf.Graph()
with graph1.as_default():
# Input data. For the training data, we use a placeholder that will be fed
# at run time with a training minibatch.
tf_train_dataset = tf.placeholder(tf.float32,
shape=(batch_size, image_size * image_size))
tf_train_labels = tf.placeholder(tf.float32, shape=(batch_size, num_labels))
tf_valid_dataset = tf.constant(valid_dataset)
tf_test_dataset = tf.constant(test_dataset)
# Variables.
weights_RELU = tf.Variable(
tf.truncated_normal([image_size * image_size, num_RELU]))
biases_RELU = tf.Variable(tf.zeros([num_RELU]))
weights_layer1 = tf.Variable(
tf.truncated_normal([num_RELU, num_labels]))
biases_layer1 = tf.Variable(tf.zeros([num_labels]))
# Training computation.
logits_RELU = tf.matmul(tf_train_dataset, weights_RELU) + biases_RELU
RELU_vec = tf.nn.relu(logits_RELU)
logits_layer = tf.matmul(RELU_vec, weights_layer1) + biases_layer1
loss = tf.reduce_mean(
tf.nn.softmax_cross_entropy_with_logits(logits_layer, tf_train_labels))
# Optimizer.
optimizer = tf.train.GradientDescentOptimizer(0.3).minimize(loss)
# Predictions for the training, validation, and test data.
train_prediction = tf.nn.softmax(logits_layer)
valid_prediction = tf.nn.softmax(
tf.matmul(tf.nn.relu((tf.matmul(tf_valid_dataset, weights_RELU) + biases_RELU)),weights_layer1)+biases_layer1)
test_prediction =tf.nn.softmax(
tf.matmul(tf.nn.relu((tf.matmul(tf_test_dataset, weights_RELU) + biases_RELU)),weights_layer1)+biases_layer1)
接着是
import datetime
startTime = datetime.datetime.now()
num_steps = 301 #3001
with tf.Session(graph=graph1) as session:
tf.initialize_all_variables().run()
print("Initialized")
for step in range(num_steps):
# Pick an offset within the training data, which has been randomized.
# Note: we could use better randomization across epochs.
offset = (step * batch_size) % (train_labels.shape[0] - batch_size)
# Generate a minibatch.
batch_data = train_dataset[offset:(offset + batch_size), :]
batch_labels = train_labels[offset:(offset + batch_size), :]
# Prepare a dictionary telling the session where to feed the minibatch.
# The key of the dictionary is the placeholder node of the graph to be fed,
# and the value is the numpy array to feed to it.
feed_dict = {tf_train_dataset : batch_data, tf_train_labels : batch_labels}
_, l, predictions = session.run(
[optimizer, loss, train_prediction], feed_dict=feed_dict)
if (step % 500 == 0):
print("Minibatch loss at step %d: %f" % (step, l))
print("Minibatch accuracy: %.1f%%" % accuracy(predictions, batch_labels))
print("Validation accuracy: %.1f%%" % accuracy(
valid_prediction.eval(), valid_labels))
print("Test accuracy: %.1f%%" % accuracy(test_prediction.eval(), test_labels))
tf.Print(logits_RELU,[logits_RELU],message="This is logits:") #this in itself doesn't print anything
logits_RELU.eval() #this is what i tried reading the other post
x = datetime.datetime.now() - startTime
print(x)
返回以下错误
InvalidArgumentError Traceback (most recent call
last) <ipython-input-75-b79445d934e0> in <module>()
29 print("Test accuracy: %.1f%%" % accuracy(test_prediction.eval(), test_labels))
30 tf.Print(logits_RELU,[logits_RELU],message="This is logits:")
---> 31 logits_RELU.eval()
32 x = datetime.datetime.now() - startTime
33 print(x)
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/python/framework/ops.pyc
in eval(self, feed_dict, session)
463
464 """
--> 465 return _eval_using_default_session(self, feed_dict, self.graph, session)
466
467
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/python/framework/ops.pyc
in _eval_using_default_session(tensors, feed_dict, graph, session)
3095 "the tensor's graph is different from the
session's " 3096 "graph.")
-> 3097 return session.run(tensors, feed_dict) 3098 3099
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/python/client/session.pyc
in run(self, fetches, feed_dict)
313 `Tensor` that doesn't exist.
314 """
--> 315 return self._run(None, fetches, feed_dict)
316
317 def partial_run(self, handle, fetches, feed_dict=None):
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/python/client/session.pyc
in _run(self, handle, fetches, feed_dict)
509 # Run request and get response.
510 results = self._do_run(handle, target_list, unique_fetches,
--> 511 feed_dict_string)
512
513 # User may have fetched the same tensor multiple times, but we
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/python/client/session.pyc
in _do_run(self, handle, target_list, fetch_list, feed_dict)
562 if handle is None:
563 return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
--> 564 target_list)
565 else:
566 return self._do_call(_prun_fn, self._session, handle, feed_dict,
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/python/client/session.pyc
in _do_call(self, fn, *args)
584 # pylint: disable=protected-access
585 raise errors._make_specific_exception(node_def, op, error_message,
--> 586 e.code)
587 # pylint: enable=protected-access
588 six.reraise(e_type, e_value, e_traceback)
InvalidArgumentError: You must feed a value for placeholder tensor
'Placeholder' with dtype float and shape [128,784] [[Node:
Placeholder = Placeholder[dtype=DT_FLOAT, shape=[128,784],
_device="/job:localhost/replica:0/task:0/cpu:0"]()]] Caused by op u'Placeholder', defined at: File
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/runpy.py",
line 162, in _run_module_as_main
"__main__", fname, loader, pkg_name) File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/runpy.py",
line 72, in _run_code
exec code in run_globals File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/ipykernel/__main__.py",
line 3, in <module>
app.launch_new_instance() File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/traitlets/config/application.py",
line 596, in launch_instance
app.start() File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/ipykernel/kernelapp.py",
line 442, in start
ioloop.IOLoop.instance().start() File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/zmq/eventloop/ioloop.py",
line 162, in start
super(ZMQIOLoop, self).start() File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tornado/ioloop.py",
line 883, in start
handler_func(fd_obj, events) File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tornado/stack_context.py",
line 275, in null_wrapper
return fn(*args, **kwargs) File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py",
line 440, in _handle_events
self._handle_recv() File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py",
line 472, in _handle_recv
self._run_callback(callback, msg) File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py",
line 414, in _run_callback
callback(*args, **kwargs) File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tornado/stack_context.py",
line 275, in null_wrapper
return fn(*args, **kwargs) File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/ipykernel/kernelbase.py",
line 276, in dispatcher
return self.dispatch_shell(stream, msg) File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/ipykernel/kernelbase.py",
line 228, in dispatch_shell
handler(stream, idents, msg) File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/ipykernel/kernelbase.py",
line 391, in execute_request
user_expressions, allow_stdin) File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/ipykernel/ipkernel.py",
line 199, in do_execute
shell.run_cell(code, store_history=store_history, silent=silent) File
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/IPython/core/interactiveshell.py",
line 2723, in run_cell
interactivity=interactivity, compiler=compiler, result=result) File
"/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/IPython/core/interactiveshell.py",
line 2825, in run_ast_nodes
if self.run_code(code, result): File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/IPython/core/interactiveshell.py",
line 2885, in run_code
exec(code_obj, self.user_global_ns, self.user_ns) File "<ipython-input-60-eea4738bb583>", line 9, in <module>
shape=(batch_size, image_size * image_size)) File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.py",
line 742, in placeholder
name=name) File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.py",
line 583, in _placeholder
name=name) File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/python/ops/op_def_library.py",
line 655, in apply_op
op_def=op_def) File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/python/framework/ops.py",
line 2040, in create_op
original_op=self._default_original_op, op_def=op_def) File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/python/framework/ops.py",
line 1087, in __init__
self._traceback = _extract_stack()
答案 0 :(得分：1)
当您使用tf.placeholder时，只要您尝试在会话中运行某些操作，就必须提供它们。 现在你需要占位符如下：
tf_train_dataset = tf.placeholder(tf.float32,shape=(batch_size, image_size * image_size))
tf_train_labels = tf.placeholder(tf.float32, shape=(batch_size, num_labels))
当您运行会话时，您必须像在
中一样提供它们_, l, predictions = session.run([optimizer, loss, train_prediction], feed_dict=feed_dict)
但您可以看到，当您拨打Tensor.eval()时就像在test_prediction.eval()中一样，您没有为占位符提供信息。
记得。只要你有占位符，你就必须在每次想要评估张量或选择时提供它们。