Relation-Classification-using-Bidirectional-LSTM-Tree
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Sshanu
Invalid Argument Error
Hi Shanu
I tried Model3v1 for 10 samples. Accordingly I generated train_paths and when i run, I get the below error. PLease let know. I have attached the source file too - model3v1.txt
File "
InvalidArgumentError (see above for traceback): slice index 1 of dimension 0 out of bounds. [[Node: gradients_1/hidden_layer_seq/while_3/strided_slice_grad/StridedSliceGrad = StridedSliceGrad[Index=DT_INT32, T=DT_FLOAT, begin_mask=0, ellipsis_mask=0, end_mask=0, new_axis_mask=0, shrink_axis_mask=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](gradients_1/hidden_layer_seq/while_3/strided_slice_grad/StridedSliceGrad/StackPopV2, gradients_1/hidden_layer_seq/while_3/strided_slice_grad/StridedSliceGrad/StackPopV2_1, gradients_1/hidden_layer_seq/while_3/strided_slice_grad/StridedSliceGrad/StackPopV2_2, gradients_1/hidden_layer_seq/while_3/strided_slice_grad/StridedSliceGrad/Const_3, gradients_1/hidden_layer_seq/while_3/MatMul_grad/tuple/control_dependency)]]
Exact error and the code line InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'input/sp_childs' with dtype int32 and shape [5,2,20,20]
For complete model training ---> 29 _, _loss, step, _summary = sess.run([train_op, total_loss, global_step_dep, summary], feed_dict)
first check whether [[childs_path1[k], childs_path2[k]] for k in range(s, end)] has the same dimension as [5, 2, 20, 20] and also the data type
Thank you Shanu for the response. I tried for a small sample as it was slow. But now i tried with all 8000 and am running them in python2 All pickles are written with python2
Now I get this error. InvalidArgumentError (see above for traceback): Inputs to operation gradients_1/AddN_1101 of type AddN must have the same size and shape. Input 0: [2,20,1,100] != input 1: [2,1,1,100 This is in model3v2, this line of code For complete model training _, _loss, step, _summary = sess.run([train_op, total_loss, global_step_dep, summary], feed_dict)
Kindly help
please try using python 3.
Just use printing the shapes of this tensors, then debug the code
Hey shanu, why should there be a change in dimensions of the tensors, if i am using the same data as yours @arunzz were you able to solve the problem?
Can you please post the error or for which tensors dimension problem is occurring?
Yes Use python 3 It worked. No changes to any dimensions. But the label encoding also has to be passed into relation encoder. That part is missing i think
On Jun 15, 2018, at 11:33 AM, Shanu Kumar [email protected] wrote:
Can you please post the error or for which tensors dimension problem is occurring?
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@arunzz can you share some more insights, actually i am currently learning about it meanwhile i am working on this. It will be a great help. or maybe you can share your version.
Hi
Shanu is our guru :) He wrote the entire thing.
Regards Arun
On Fri, Jun 15, 2018 at 2:51 PM, NeverInAsh [email protected] wrote:
@arunzz https://github.com/arunzz can you share some more insights, actually i am currently learning about it meanwhile i am working on this. It will be a great help. or maybe you can share your version.
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@arunzz @NeverInAsh I'm wondering what you guys did to fix the error? I am running python 3
Just python3 Initialize global variables after loading glove embeddings.
On Jul 2, 2018, at 7:59 PM, enmatics [email protected] wrote:
@arunzz @NeverInAsh I'm wondering what you guys did to fix the error? I am running python 3
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@arunzz I have meet the same problem. I am running python 3, but the problem still exist. Can you attached the worked model3v2 source file?
@arunzz when I don't init glove embedding in your source file, it will exist the error: InvalidArgumentError (see above for traceback): slice index 1 of dimension 0 out of bounds. [[Node: gradients_1/hidden_layer_seq/while_3/strided_slice_grad/StridedSliceGrad = StridedSliceGrad[Index=DT_INT32, T=DT_FLOAT, begin_mask=0, ellipsis_mask=0, end_mask=0, new_axis_mask=0, shrink_axis_mask=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"]
when I init glove embedding, it will exist the error: InvalidArgumentError (see above for traceback): Inputs to operation gradients_1/AddN_1101 of type AddN must have the same size and shape. Input 0: [2,20,1,100] != input 1: [2,1,1,100]
@arunzz When I use tensorflow 1.12.0, it will lead "ArithmeticOptimize" error. Then I replaced the version of tensorflow 1.8.0. and worked. But it will occur "concat" error and "hidden_layer" error. Then I replaced the version of tensorflow 1.10.0. Your source file finally worked.
@arunzz in model3v2 model = tf.train.latest_checkpoint(model_dir) saver.restore(sess, model) when I try to restore the error says 👎 ValueError: Can't load save_path when it is None. Please help
