我有一个非常简单的神经网络的代码（这段代码实际上是一个简单问题的改编）：
import numpy as np
import tensorflow as tf
with tf.device("cpu:0"):
sess = tf.InteractiveSession()
nNodes = 3
inputDim = 1
rowIdxs = np.zeros([nNodes, nNodes])
colIdxs = np.zeros([nNodes, nNodes])
for rowIdx in range(nNodes):
for colIdx in range(nNodes):
rowIdxs[rowIdx, colIdx] = rowIdx
colIdxs[rowIdx, colIdx] = colIdx
rowIdxs = np.reshape(rowIdxs, [-1])
colIdxs = np.reshape(colIdxs, [-1])
# build a matrix with nNodes x nNodes elements
# with each row i containing the distance from node i to all the other nodes
distances = np.zeros([nNodes, nNodes])
for i in range(nNodes):
for j in range(nNodes):
distances[i, j] = ((rowIdxs[i] - rowIdxs[j]) ** 2 + (colIdxs[i] - colIdxs[j]) ** 2)
print('distances=', distances)
# tensorflow constant from distances matrix
distances_ = tf.constant(distances, dtype=tf.float32)
# w corresponds to a weight matrix in a neural network
w = tf.random_uniform((nNodes, inputDim), 0.0, 1.0)
# x corresponds to the input to the network
x = tf.random_uniform((1, inputDim), 0.0, 1.0)
xx = tf.tile(x, [nNodes,1])
print('w', w.shape)
print('x', x.shape)
print('xx', xx.shape)
# differences between weights and input vector
diff = tf.reduce_sum(tf.abs(tf.subtract(xx, w)), 1)
print('diff.shape', diff.shape)
# index of the best matching unit
bmu = tf.arg_min(diff, 0)
# Now I need to access the distances from BMU to the other nodes
slice = tf.slice(distances_, [bmu, 0], [bmu, -1])
sess.run(tf.global_variables_initializer())
sess.run(slice)
print('slice=', slice.eval())
print('diff', diff.eval())
print('bmu=', bmu.eval())
基本上，给定输入x，将其与权重w进行比较，并选择具有最小差异的节点BMU。
我对该代码有几个问题：
1。有时它会毫无错误地工作，但有时它会引发异常。
当它不起作用时，输出为：
distances=
[[ 0. 1. 4.]
[ 1. 0. 1.]
[ 4. 1. 0.]]
w (3, 1)
x (1, 1)
xx (3, 1)
diff.shape (3,)
InvalidArgumentError (see above for traceback): Expected size[0] in [0, 1], but got 2
[[Node: Slice = Slice[Index=DT_INT64, T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](Const, Slice/begin, Slice/size)]]
完整堆栈如下：
Traceback (most recent call last):
File "D:\python\lib\site-packages\tensorflow\python\client\session.py", line 1022, in _do_call
return fn(*args)
File "D:\python\lib\site-packages\tensorflow\python\client\session.py", line 1004, in _run_fn
status, run_metadata)
File "D:\python\lib\contextlib.py", line 66, in __exit__
next(self.gen)
File "D:\python\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 469, in raise_exception_on_not_ok_status
pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: Expected size[0] in [0, 1], but got 2
[[Node: Slice = Slice[Index=DT_INT64, T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](Const, Slice/begin, Slice/size)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "D:/workspace/LiClipse Workspace/kerasPython/exercises/testIndexing.py", line 44, in <module>
sess.run(slice)
File "D:\python\lib\site-packages\tensorflow\python\client\session.py", line 767, in run
run_metadata_ptr)
File "D:\python\lib\site-packages\tensorflow\python\client\session.py", line 965, in _run
feed_dict_string, options, run_metadata)
File "D:\python\lib\site-packages\tensorflow\python\client\session.py", line 1015, in _do_run
target_list, options, run_metadata)
File "D:\python\lib\site-packages\tensorflow\python\client\session.py", line 1035, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Expected size[0] in [0, 1], but got 2
[[Node: Slice = Slice[Index=DT_INT64, T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](Const, Slice/begin, Slice/size)]]
Caused by op 'Slice', defined at:
File "D:/workspace/LiClipse Workspace/kerasPython/exercises/testIndexing.py", line 39, in <module>
slice = tf.slice(distances_, [bmu, 0], [bmu, -1])
File "D:\python\lib\site-packages\tensorflow\python\ops\array_ops.py", line 561, in slice
return gen_array_ops._slice(input_, begin, size, name=name)
File "D:\python\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 3053, in _slice
name=name)
File "D:\python\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 763, in apply_op
op_def=op_def)
File "D:\python\lib\site-packages\tensorflow\python\framework\ops.py", line 2395, in create_op
original_op=self._default_original_op, op_def=op_def)
File "D:\python\lib\site-packages\tensorflow\python\framework\ops.py", line 1264, in __init__
self._traceback = _extract_stack()
InvalidArgumentError (see above for traceback): Expected size[0] in [0, 1], but got 2
[[Node: Slice = Slice[Index=DT_INT64, T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](Const, Slice/begin, Slice/size)]]
工作时
w (3, 1)
x (1, 1)
xx (3, 1)
diff.shape (3,)
slice= [[ 1. 0. 1.]]
diff [ 0.29777944 0.08669317 0.09722018]
bmu= 0
bmu错误，应该是1，但切片是正确的。
有时我会这样：
w (3, 1)
x (1, 1)
xx (3, 1)
diff.shape (3,)
slice= []
diff [ 0.33319855 0.12426794 0.49753141]
bmu= 1
bmu为1，但切片为空。
2。当我切换到GPU时，我有一个例外，告诉我我不能使用bmu进行索引。
从with tf.device("gpu:0"):开始，我得到了这个：
InvalidArgumentError (see above for traceback): Cannot assign a device to node 'Slice/size': Could not satisfy explicit device specification '/device:GPU:0' because no supported kernel for GPU devices is available.
[[Node: Slice/size = Pack[N=2, T=DT_INT64, axis=0, _device="/device:GPU:0"](ArgMin, Slice/size/1)]]
完整的堆栈跟踪如下：
Traceback (most recent call last):
File "D:\python\lib\site-packages\tensorflow\python\client\session.py", line 1022, in _do_call
return fn(*args)
File "D:\python\lib\site-packages\tensorflow\python\client\session.py", line 1004, in _run_fn
status, run_metadata)
File "D:\python\lib\contextlib.py", line 66, in __exit__
next(self.gen)
File "D:\python\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 469, in raise_exception_on_not_ok_status
pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: Cannot assign a device to node 'Slice/size': Could not satisfy explicit device specification '/device:GPU:0' because no supported kernel for GPU devices is available.
[[Node: Slice/size = Pack[N=2, T=DT_INT64, axis=0, _device="/device:GPU:0"](ArgMin, Slice/size/1)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "D:/workspace/LiClipse Workspace/kerasPython/exercises/testIndexing.py", line 45, in <module>
sess.run(slice)
File "D:\python\lib\site-packages\tensorflow\python\client\session.py", line 767, in run
run_metadata_ptr)
File "D:\python\lib\site-packages\tensorflow\python\client\session.py", line 965, in _run
feed_dict_string, options, run_metadata)
File "D:\python\lib\site-packages\tensorflow\python\client\session.py", line 1015, in _do_run
target_list, options, run_metadata)
File "D:\python\lib\site-packages\tensorflow\python\client\session.py", line 1035, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Cannot assign a device to node 'Slice/size': Could not satisfy explicit device specification '/device:GPU:0' because no supported kernel for GPU devices is available.
[[Node: Slice/size = Pack[N=2, T=DT_INT64, axis=0, _device="/device:GPU:0"](ArgMin, Slice/size/1)]]
Caused by op 'Slice/size', defined at:
File "D:/workspace/LiClipse Workspace/kerasPython/exercises/testIndexing.py", line 40, in <module>
slice = tf.slice(distances_, [bmu, 0], [bmu, -1])
File "D:\python\lib\site-packages\tensorflow\python\ops\array_ops.py", line 561, in slice
return gen_array_ops._slice(input_, begin, size, name=name)
File "D:\python\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 3053, in _slice
name=name)
File "D:\python\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 491, in apply_op
preferred_dtype=default_dtype)
File "D:\python\lib\site-packages\tensorflow\python\framework\ops.py", line 716, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "D:\python\lib\site-packages\tensorflow\python\ops\array_ops.py", line 923, in _autopacking_conversion_function
return _autopacking_helper(v, inferred_dtype, name or "packed")
File "D:\python\lib\site-packages\tensorflow\python\ops\array_ops.py", line 886, in _autopacking_helper
return gen_array_ops._pack(elems_as_tensors, name=scope)
File "D:\python\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 2041, in _pack
result = _op_def_lib.apply_op("Pack", values=values, axis=axis, name=name)
File "D:\python\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 763, in apply_op
op_def=op_def)
File "D:\python\lib\site-packages\tensorflow\python\framework\ops.py", line 2395, in create_op
original_op=self._default_original_op, op_def=op_def)
File "D:\python\lib\site-packages\tensorflow\python\framework\ops.py", line 1264, in __init__
self._traceback = _extract_stack()
InvalidArgumentError (see above for traceback): Cannot assign a device to node 'Slice/size': Could not satisfy explicit device specification '/device:GPU:0' because no supported kernel for GPU devices is available.
[[Node: Slice/size = Pack[N=2, T=DT_INT64, axis=0, _device="/device:GPU:0"](ArgMin, Slice/size/1)]]
我无法理解发生了什么：我有一个想法，但在文档或其他任何地方找不到任何参考。可能是我使用了错误的关键字。
有没有人可以帮助我？
答案 0 :(得分：0)
tf.slice 函数 (see TF1.15 doc) 将切片的 size 作为第三个参数，因此行 slice = tf.slice(distances_, [bmu, 0], [bmu, -1]) 必须替换为
slice = tf.slice(distances_, [bmu, 0], [1, -1])
仅当 bmu 大于 distances_ 中行数的一半时才会出现错误，因为在这种情况下无法提取给定大小的切片。否则计算不会失败但它是不正确的，因为您没有提取一行。