尝试自学神经网络,我已经开始在deeplearning.net上通过Theano教程。我刚刚遇到一个我没想到的错误,因为我已经从教程中逐字复制并粘贴了每一行代码。我确定什么是错的是小事我只是看着它但是任何帮助都会非常感激。谢谢
http://deeplearning.net/software/theano/tutorial/examples.html#copying-functions
import theano
import theano.tensor as T
state = theano.shared(0)
inc = T.iscalar('inc')
accumulator = theano.function([inc], state, updates=[(state, state+inc)])
accumulator(10)
print(state.get_value())
new_state = theano.shared(0)
new_accumulator = accumulator.copy(swap={state:new_state})
new_accumulator(100)
print(state.get_value())
print(new_state.get_value())
null_accumulator = accumulator.copy(delete_updates=True)
---------------------------------------------------------------------------
UnusedInputError Traceback (most recent call last)
<ipython-input-20-5d1acb597345> in <module>()
----> 1 null_accumulator = accumulator.copy(delete_updates=True)
/home/mcamp/anaconda3/lib/python3.5/site-packages/theano/compile/function_module.py in copy(self, share_memory, swap, delete_updates, name, profile)
719 # can contain inplace. DebugMode check
720 # that.
--> 721 accept_inplace=True,
722 ).create(input_storage,
723 storage_map=new_storage_map)
/home/mcamp/anaconda3/lib/python3.5/site-packages/theano/compile/function_module.py in __init__(self, inputs, outputs, mode, accept_inplace, function_builder, profile, on_unused_input, fgraph, output_keys)
1413
1414 # Check if some input variables are unused
-> 1415 self._check_unused_inputs(inputs, outputs, on_unused_input)
1416
1417 # Make a list of (SymbolicInput|SymblicInputKits, indices,
/home/mcamp/anaconda3/lib/python3.5/site-packages/theano/compile/function_module.py in _check_unused_inputs(self, inputs, outputs, on_unused_input)
1551 elif on_unused_input == 'raise':
1552 raise UnusedInputError(msg % (inputs.index(i),
-> 1553 i.variable, err_msg))
1554 else:
1555 raise ValueError("Invalid value for keyword "
UnusedInputError: theano.function was asked to create a function computing outputs given certain inputs, but the provided input variable at index 0 is not part of the computational graph needed to compute the outputs: inc.
To make this error into a warning, you can pass the parameter on_unused_input='warn' to theano.function. To disable it completely, use on_unused_input='ignore'.