Can you share the whole code?
There may be an issue in the way you are calling verify_grad.
Or maybe you are defining a scalar op, operating on a theano.scalar, and not a
theano.tensor, in which case you should use theano.scalar.tanh instead.
On Wed, Oct 26, 2016, mrinmoy maity wrote:
> Here's the definition of grad() function inside Op class.
>
> def grad(self, inputs, grads):
> x, = inputs
> gz, = grads
> # rval = theano.tensor.as_tensor_variable(gz *
> (1-numpy.power(theano.tensor.tanh(x), 2))) # Doesn't work
> # rval = gz * math.tanh(float(x)) # Doesn't work
> # rval = 2 * numpy.power(x, 2) # Works
> rval = gz * theano.tensor.tanh(x) # Doesn't work
> return [rval]
>
>
> And here's the full backtrace:
>
> *Traceback (most recent call last):*
>
> File "<ipython-input-23-cb484da32904>", line 1, in <module>
>
> runfile('/Users/mrins/anaconda/lib/python3.4/site-packages/theano/tensor/nnet/step.py',
> wdir='/Users/mrins/anaconda/lib/python3.4/site-packages/theano/tensor/nnet')
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/spyderlib/widgets/externalshell/sitecustomize.py",
> line 699, in runfile
> execfile(filename, namespace)
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/spyderlib/widgets/externalshell/sitecustomize.py",
> line 88, in execfile
> exec(compile(open(filename, 'rb').read(), filename, 'exec'), namespace)
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/tensor/nnet/step.py",
> line 168, in <module>
> test_VectorBinarization()
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/tensor/nnet/step.py",
> line 163, in test_VectorBinarization
> test_vector_binarize.test_grad()
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/tensor/nnet/step.py",
> line 149, in test_grad
> verify_grad(binarize, [numpy.random.rand(5, 7, 2)])
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/tests/unittest_tools.py",
> line 91, in verify_grad
> T.verify_grad(op, pt, n_tests, rng, *args, **kwargs)
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/gradient.py",
> line 1695, in verify_grad
> disconnected_inputs='ignore')
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/gradient.py",
> line 553, in grad
> grad_dict, wrt, cost_name)
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/gradient.py",
> line 1317, in _populate_grad_dict
> rval = [access_grad_cache(elem) for elem in wrt]
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/gradient.py",
> line 1317, in <listcomp>
> rval = [access_grad_cache(elem) for elem in wrt]
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/gradient.py",
> line 1272, in access_grad_cache
> term = access_term_cache(node)[idx]
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/gradient.py",
> line 1106, in access_term_cache
> new_output_grads)
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/gof/op.py", line
> 700, in L_op
> return self.grad(inputs, output_grads)
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/tensor/elemwise.py",
> line 671, in grad
> rval = self._bgrad(inputs, ograds)
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/tensor/elemwise.py",
> line 786, in _bgrad
> ret.append(transform(scalar_igrad))
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/tensor/elemwise.py",
> line 778, in transform
> *[transform(ipt) for ipt in node.inputs])
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/tensor/elemwise.py",
> line 778, in <listcomp>
> *[transform(ipt) for ipt in node.inputs])
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/tensor/elemwise.py",
> line 778, in transform
> *[transform(ipt) for ipt in node.inputs])
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/gof/op.py", line
> 604, in __call__
> node = self.make_node(*inputs, **kwargs)
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/tensor/elemwise.py",
> line 586, in make_node
> DimShuffle, *inputs)
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/tensor/elemwise.py",
> line 528, in get_output_info
> for i in inputs])
>
> File
> "/Users/mrins/anaconda/lib/python3.4/site-packages/theano/tensor/basic.py",
> line 1200, in make_node
> *assert isinstance(t.type, TensorType)*
>
> AssertionError
>
>
> Regards,
> Mrinmoy
>
> On Wed, Oct 26, 2016 at 6:50 PM, Frédéric Bastien <
> [email protected]> wrote:
>
> > Can you give the full stack trace and your grad() method? There is
> > something strange. The Theano variable X seem malformed.
> >
> > The problem could also be in your make node that build a bad output
> > variable?
> >
> > Fred
> >
> > On Wed, Oct 26, 2016 at 5:47 PM, mrinmoy maity <[email protected]> wrote:
> >
> >>
> >> I am trying experiment with a new Op in Theano. While defining the grad()
> >> method, a function f(theano.tensor.tanh(x)) is used where x is the input.
> >> However, internally its hitting an assert here:
> >>
> >>
> >> File "~/anaconda/lib/python3.4/site-packages/theano/tensor/basic.py",
> >> line 1198, in make_node
> >> assert isinstance(t.type, TensorType)
> >>
> >>
> >> The partial backtrace is given here:
> >>
> >>
> >> File "~/anaconda/lib/python3.4/site-packages/theano/gof/op.py", line
> >> 604, in __call__
> >> node = self.make_node(*inputs, **kwargs)
> >>
> >> File "~/anaconda/lib/python3.4/site-packages/theano/tensor/elemwise.py",
> >> line 586, in make_node
> >> DimShuffle, *inputs)
> >>
> >> File "~/anaconda/lib/python3.4/site-packages/theano/tensor/elemwise.py",
> >> line 528, in get_output_info
> >> for i in inputs])
> >>
> >> File "~/anaconda/lib/python3.4/site-packages/theano/tensor/basic.py",
> >> line 1198, in make_node
> >> assert isinstance(t.type, TensorType)
> >>
> >> AssertionError
> >>
> >>
> >> The t.type here is 'float64' instead of a Tensortype. The issue is easily
> >> reproducible with using tanh inside grad().
> >> Note that I'm not using 'tanh' op here, rather using tanh in grad(). Also
> >> encapsulating return from grad() using theano.tensor.as_tensor_variable()
> >> doesn't work here.
> >>
> >>
> >> Please let me know if there's a workaround for this.
> >>
> >>
> >> Regards,
> >> Mrinmoy
> >>
> >>
> >> --
> >>
> >> ---
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> >>
> >
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