Caroline Etienne
2018-04-11 12:17:41 UTC
Hello,
I would like to have one variable representing the huge list of
TensorVariable provided with dic_in and dic_out. But I don't manage to do
that with the inner function of theano scan.
def inner_function(dic_in, dic_out, *args):
input_t0, input_t1, input_t2 = dic_in
cell_tm1, cell_tm2, cell_tm3 = dic_out
and not
def inner_function(input_t0, input_t1, input_t2, cell_tm1, cell_tm2,
cell_tm3, *args):
nb_time_steps = 3
jump_step = 1
step_list_in = [i for i in range(0, nb_time_steps, jump_step)]
step_list_out = [i for i in range(-nb_time_steps, 0, jump_step)]
dic_in = {'input': sequences, 'taps': step_list_in}
dic_out = {'initial': cell_init, 'taps': step_list_out}
non_seqs =
results, updates = theano.scan(fn=inner_function, sequences = [dic_in],
outputs_info = [dic_out],
go_backwards=self.backwards,
truncate_gradient=self.gradient_steps,
non_sequences = non_seqs, strict=True)[0]
Would someone have some ideas ?
Thank you !
I would like to have one variable representing the huge list of
TensorVariable provided with dic_in and dic_out. But I don't manage to do
that with the inner function of theano scan.
def inner_function(dic_in, dic_out, *args):
input_t0, input_t1, input_t2 = dic_in
cell_tm1, cell_tm2, cell_tm3 = dic_out
and not
def inner_function(input_t0, input_t1, input_t2, cell_tm1, cell_tm2,
cell_tm3, *args):
nb_time_steps = 3
jump_step = 1
step_list_in = [i for i in range(0, nb_time_steps, jump_step)]
step_list_out = [i for i in range(-nb_time_steps, 0, jump_step)]
dic_in = {'input': sequences, 'taps': step_list_in}
dic_out = {'initial': cell_init, 'taps': step_list_out}
non_seqs =
results, updates = theano.scan(fn=inner_function, sequences = [dic_in],
outputs_info = [dic_out],
go_backwards=self.backwards,
truncate_gradient=self.gradient_steps,
non_sequences = non_seqs, strict=True)[0]
Would someone have some ideas ?
Thank you !
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