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我想设计这样的损失函数:Tensorflow:tf.argmax和切片
sum((y[argmax(y_)] - y_[argmax(y_)])²)
我没有找到一个方法来做到y[argmax(y_)]
。我试过y[k]
,y[:,k]
和y[None,k]
这些工作都没有。这是我的代码:
Na = 3
x = tf.placeholder(tf.float32, [None, 2])
W = tf.Variable(tf.zeros([2, Na]))
b = tf.Variable(tf.zeros([Na]))
y = tf.nn.relu(tf.matmul(x, W) + b)
y_ = tf.placeholder(tf.float32, [None, 3])
k = tf.argmax(y_, 1)
diff = y[k] - y_[k]
loss = tf.reduce_sum(tf.square(diff))
和错误:
File "/home/ncarrara/phd/code/cython/robotnavigation/ftq/cftq19.py", line 156, in <module>
diff = y[k] - y_[k]
File "/home/ncarrara/miniconda3/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.py", line 499, in _SliceHelper
name=name)
File "/home/ncarrara/miniconda3/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.py", line 663, in strided_slice
shrink_axis_mask=shrink_axis_mask)
File "/home/ncarrara/miniconda3/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.py", line 3515, in strided_slice
shrink_axis_mask=shrink_axis_mask, name=name)
File "/home/ncarrara/miniconda3/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
op_def=op_def)
File "/home/ncarrara/miniconda3/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2508, in create_op
set_shapes_for_outputs(ret)
File "/home/ncarrara/miniconda3/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1873, in set_shapes_for_outputs
shapes = shape_func(op)
File "/home/ncarrara/miniconda3/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1823, in call_with_requiring
return call_cpp_shape_fn(op, require_shape_fn=True)
File "/home/ncarrara/miniconda3/lib/python2.7/site-packages/tensorflow/python/framework/common_shapes.py", line 610, in call_cpp_shape_fn
debug_python_shape_fn, require_shape_fn)
File "/home/ncarrara/miniconda3/lib/python2.7/site-packages/tensorflow/python/framework/common_shapes.py", line 676, in _call_cpp_shape_fn_impl
raise ValueError(err.message)
ValueError: Shape must be rank 1 but is rank 2 for 'strided_slice' (op: 'StridedSlice') with input shapes: [?,3], [1,?], [1,?], [1].
看起来不错,但现在我不确定是否足以验证您的答案,无论如何,谢谢! –
@nicolascarrara我已经添加了一些解释。 – jdehesa
非常感谢,现在很清楚! –