Does anybody have experience with how to get the shape of a Symbol using infer_shape?

hi @samhodge sorry i have been busy and havent gotten a chance to look at your changes. Have you looked at infer_shape documentation ?

i think you should be able to use infer_shape without any arguments

the shape should be inferred when data is bound to the symbolic inputs to the model

I will try again, I looked

its not very clear from the documentation. maybe we should add an example to the documentation.

/home/samh/dev/MXNet-Gluon-Style-Transfer/net.py:332: UserWarning: Cannot decide shape for the following arguments (0s in shape means unknown dimensions). Consider providing them as input:

data: ()

in_shapes,out_shapes,arg_shapes= X.infer_shape()

data: ()

in_shapes,out_shapes,arg_shapes= X.infer_shape()

that is not a good start

With this

`class Inspiration(HybridBlock):

""" Inspiration Layer (from MSG-Net paper)

tuning the featuremap with target Gram Matrix

ref https://arxiv.org/abs/1703.06953

"""

def**init**(self, C, B=1, ctx=mx.cpu(0)):

super(Inspiration, self).**init**()

""" Inspiration Layer (from MSG-Net paper)

tuning the featuremap with target Gram Matrix

ref https://arxiv.org/abs/1703.06953

"""

def

super(Inspiration, self).

```
# B is equal to 1 or input mini_batch
self.C = C
self.B = B
self.weight = self.collect_params().get('weight', shape=(1,self.C,self.C),
init=mx.initializer.Uniform(),
allow_deferred_init=True)
self.gram = self.collect_params().get('gram', shape=(self.B,self.C,self.C),
init=mx.initializer.Uniform(),
allow_deferred_init=True,
lr_mult=0)
self.weight.initialize(ctx=ctx)
self.gram.initialize(ctx=ctx)
def setTarget(self, target):
self.gram.set_data(target)
def hybrid_forward(self, F, X, gram, weight):
P = F.batch_dot(F.broadcast_to(weight, shape=(self.gram.shape)), gram)
if not isinstance(X,symbol.Symbol):
return F.batch_dot(F.SwapAxis(P,1,2).broadcast_to((X.shape[0], self.C, self.C)), X.reshape((0,0,X.shape[2]*X.shape[3]))).reshape(X.shape)
else:
#print "Hooppla", interals
#for i in dir(interals):
# print "kk:", i
in_shapes,out_shapes,arg_shapes= X.infer_shape(self.gram.shape)
#print out_shapes
#raise Exception
#arg_shapes, out_shapes, aux_shapes = interals.infer_shape(self.gram.shape)
#print "A", arg_shapes, "O", out_shapes, "AU", aux_shapes
return F.batch_dot(F.SwapAxis(P,1,2).broadcast_to((in_shapes[0], self.C, self.C)), X.reshape((0,0,in_shapes[2]*in_shapes[3]))).reshape(in_shapes)
def __repr__(self):
return self.__class__.__name__ + '(' \
+ 'N x ' + str(self.C) + ')'`
```

i get the following error

terminate called after throwing an instance of 'std::logic_error'

what(): basic_string::_S_construct null not valid

Abort

what(): basic_string::_S_construct null not valid

Abort