I've set THEANO_FLAGS such that floatX=float32 and type casted to float32
throughout the code. Is there a way to set allow_convert = True so that can
convert from float64 to float32 for Variable Elemwise{add,no_inplace}.0). I'm
new to group and first post so let me know if any additional info would be
helpful.
---------------------------------------------------------------------------TypeError
Traceback (most recent call
last)/home/wilson/anaconda3/lib/python3.5/site-packages/theano/compile/pfunc.py
in rebuild_collect_shared(outputs, inputs, replace, updates, rebuild_strict,
copy_inputs_over, no_default_updates) 192 update_val =
store_into.type.filter_variable(update_val,--> 193
allow_convert=False) 194 except
TypeError:
/home/wilson/anaconda3/lib/python3.5/site-packages/theano/tensor/type.py in
filter_variable(self, other, allow_convert) 234
other=other,--> 235 self=self)) 236
TypeError: Cannot convert Type TensorType(float64, matrix) (of Variable
Elemwise{add,no_inplace}.0) into Type TensorType(float32, matrix). You can try
to manually convert Elemwise{add,no_inplace}.0 into a TensorType(float32,
matrix).
During handling of the above exception, another exception occurred:
TypeError Traceback (most recent call
last)<ipython-input-137-40e9aa6eac9d> in <module>() 78 79 t =
time()---> 80 train_g = theano.function([X, Z], cost, updates=g_updates) 81
train_d = theano.function([X, Z], cost, updates=d_updates) 82 gen =
theano.function([Z], gX)
/home/wilson/anaconda3/lib/python3.5/site-packages/theano/compile/function.py
in function(inputs, outputs, mode, updates, givens, no_default_updates,
accept_inplace, name, rebuild_strict, allow_input_downcast, profile,
on_unused_input) 324 on_unused_input=on_unused_input,
325 profile=profile,--> 326
output_keys=output_keys) 327 # We need to add the flag check_aliased
inputs if we have any mutable or 328 # borrowed used defined inputs
/home/wilson/anaconda3/lib/python3.5/site-packages/theano/compile/pfunc.py in
pfunc(params, outputs, mode, updates, givens, no_default_updates,
accept_inplace, name, rebuild_strict, allow_input_downcast, profile,
on_unused_input, output_keys) 447
rebuild_strict=rebuild_strict, 448
copy_inputs_over=True,--> 449
no_default_updates=no_default_updates) 450 # extracting the arguments
451 input_variables, cloned_extended_outputs, other_stuff = output_vars
/home/wilson/anaconda3/lib/python3.5/site-packages/theano/compile/pfunc.py in
rebuild_collect_shared(outputs, inputs, replace, updates, rebuild_strict,
copy_inputs_over, no_default_updates) 206 ' function
to remove broadcastable dimensions.') 207 --> 208 raise
TypeError(err_msg, err_sug) 209 assert update_val.type ==
store_into.type 210
TypeError: ('An update must have the same type as the original shared variable
(shared_var=<TensorType(float32, matrix)>, shared_var.type=TensorType(float32,
matrix), update_val=Elemwise{add,no_inplace}.0,
update_val.type=TensorType(float64, matrix)).', 'If the difference is related
to the broadcast pattern, you can call the tensor.unbroadcast(var,
axis_to_unbroadcast[, ...]) function to remove broadcastable dimensions.')
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