I have a python list I want to splice... I also have the theano tensor 
scalar 'i':

> i = T.lscalar()
>
>
How do I use this scalar to splice the list?
This code that used to work, no longer works:

> training_x[i * self.mini_batch_size: (i + 1) * self.mini_batch_size]
>
> I get the error: "TypeError: slice indices must be integers or None or 
have an __index__ method"
Can you please help me out?

On Thursday, July 28, 2016 at 9:49:21 PM UTC+5:30, nouiz wrote:
>
> You should compile 1 theano function per network. You can put them in a 
> list and index that list to find the good funtion to call.
>
> Fred
>
> On Thu, Jul 28, 2016 at 11:42 AM Florin <[email protected] <javascript:>> 
> wrote:
>
>> I have a similar problem:
>>
>> out = lasagne.layers.get_output(nets[index], x)
>> theano.function([index], out, givens= {x: inputs})
>>
>> I basically have a list of neural networks nets and want to dynamically 
>> select which to evaluate, depending on index. How could I do this?
>>
>> Cris
>>
>> On Tuesday, March 10, 2015 at 9:10:58 AM UTC-4, nouiz wrote:
>>
>>> Do all element of the list have the same size? If so, I would recommand 
>>> to make an ndarray with 1 extra dimensions instead of putting this in a 
>>> list. Then you can put this ndarray as a shared variable
>>>
>>> example:
>>>
>>> nd_list = numpy.ndarray(list)
>>> shared_var = theano.shared(nd_list)
>>>
>>> then you can do:
>>>
>>> shared_var[index]
>>>
>>> And use that in a Theano function.
>>>
>>> Otherwise, you can use typed list: 
>>>
>>> http://deeplearning.net/software/theano/library/typed_list.html
>>>
>>> Fred
>>>
>> On Tue, Mar 10, 2015 at 9:03 AM, Rob <[email protected]> wrote:
>>>
>> I have circumvented the problem. Rather than creating a list of tensor on 
>>>> which I apply a single theano function, I just created a list of theano 
>>>> functions (one for each tensor).
>>>>
>>>> If there are better solutions I would still love to here them.
>>>>
>>>>
>>>> On Tuesday, 10 March 2015 12:46:05 UTC, Rob wrote:
>>>>>
>>>>> I want a theano function that, given a scalar input, will return a 
>>>>> tensor stored in a list at the index of that scalar. i.e
>>>>>
>>>>> theano.function([index],list[index],givens= {x: <some function of 
>>>>> index>})
>>>>>
>>>>> where the list contains different x-dependent tensors that I want to 
>>>>> evaluate depending on the index given.
>>>>>
>>>>> This generates error: 
>>>>>
>>>>> TypeError: list indices must be integers, not TensorVariable
>>>>>
>>>>>
>>>>> I'm very new to Theano so I'm probably thinking about this problem in 
>>>>> the wrong way. I would really appreciate any advice.
>>>>>
>>>>> Rob
>>>>>
>>>> -- 
>>>>
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>

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