Traceback (most recent call last):


 "train.py", line 115, in <module>

tf.app.run()


 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 44, in run

_sys.exit(main(_sys.argv[:1] + flags_passthrough))


 "train.py", line 68, in main

second_derivatives=FLAGS.second_derivatives)


 "/home/feigao/exp/learning-to-learn/meta.py", line 398, in meta_minimize

info = self.meta_loss(make_loss, len_unroll, **kwargs)


 "/home/feigao/exp/learning-to-learn/meta.py", line 357, in meta_loss

name="unroll")


 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/control_flow_ops.py", line 2622, in while_loop

result = context.BuildLoop(cond, body, loop_vars, shape_invariants)


 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/control_flow_ops.py", line 2455, in BuildLoop

pred, body, original_loop_vars, loop_vars, shape_invariants)


 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/control_flow_ops.py", line 2405, in _BuildLoop

body_result = body(*packed_vars_for_body)


 "/home/feigao/exp/learning-to-learn/meta.py", line 337, in time_step

deltas, s_i_next = update(nets[key], fx, x_i, s_i)


 "/home/feigao/exp/learning-to-learn/meta.py", line 320, in update

deltas, state_next = zip(*[net(g, s) for g, s in zip(gradients, state)])


 "/home/feigao/exp/learning-to-learn/nn/base.py", line 142, in __call__

out = self._template(*args, **kwargs)


 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/template.py", line 266, in __call__

return self._call_func(args, kwargs, check_for_new_variables=False)


 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/template.py", line 215, in _call_func

result = self._func(*args, **kwargs)


 "/home/feigao/exp/learning-to-learn/networks.py", line 249, in _build

output, next_state = build_fn(reshaped_inputs, prev_state)


 "/home/feigao/exp/learning-to-learn/networks.py", line 209, in _build

inputs = self._preprocess(tf.expand_dims(inputs, -1))


 "/home/feigao/exp/learning-to-learn/nn/base.py", line 142, in __call__

out = self._template(*args, **kwargs)


 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/template.py", line 266, in __call__

return self._call_func(args, kwargs, check_for_new_variables=False)


 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/template.py", line 215, in _call_func

result = self._func(*args, **kwargs)


 "/home/feigao/exp/learning-to-learn/preprocess.py", line 71, in _build

return tf.concat_v2(ndims - 1, [clamped_log, sign])


 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/array_ops.py", line 1057, in concat_v2

dtype=dtypes.int32).get_shape(


 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 651, in convert_to_tensor

as_ref=False)


 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 716, in internal_convert_to_tensor

ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)


 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/constant_op.py", line 176, in _constant_tensor_conversion_function

return constant(v, dtype=dtype, name=name)


 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/constant_op.py", line 165, in constant

tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape))


 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/tensor_util.py", line 367, in make_tensor_proto

_AssertCompatible(values, dtype)


 "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/tensor_util.py", line 302, in _AssertCompatible

(dtype.name, repr(mismatch), type(mismatch).__name__))
TypeError: Expected int32, got list containing Tensors of type '_Message' instead.

Traceback (most recent call last):


 "/home/mgoerner/mwe.py", line 12, in <module>

doc = nlp(my_str)


 "/home/mgoerner/.miniconda3/envs/minerva/lib/python3.8/site-packages/spacy/language.py", line 427, in __call__

doc = self.make_doc(text)


 "/home/mgoerner/.miniconda3/envs/minerva/lib/python3.8/site-packages/spacy/language.py", line 453, in make_doc

return self.tokenizer(text)
TypeError: Argument 'string' has incorrect type (expected str, got MyString)
