GithubHelp home page GithubHelp logo

rnn's People

Contributors

tolicwang avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar

rnn's Issues

在use_attention=False会报错

在use_attention=False会报错

0-10-09 19:18:06.502392: W tensorflow/core/framework/op_kernel.cc:1502] OP_REQUIRES failed at save_restore_v2_ops.cc:184 : Not found: Key decoder_1/multi_rnn_cell/cell_0/lstm_cell/bias not found in checkpoint
Traceback (most recent call last):
File "D:\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\client\session.py", line 1356, in _do_call
return fn(*args)
File "D:\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\client\session.py", line 1341, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "D:\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\client\session.py", line 1429, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.NotFoundError: Key decoder_1/multi_rnn_cell/cell_0/lstm_cell/bias not found in checkpoint
[[{{node save/RestoreV2}}]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "D:\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\training\saver.py", line 1286, in restore
{self.saver_def.filename_tensor_name: save_path})
File "D:\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\client\session.py", line 950, in run
run_metadata_ptr)
File "D:\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\client\session.py", line 1173, in _run
feed_dict_tensor, options, run_metadata)
File "D:\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\client\session.py", line 1350, in _do_run
run_metadata)
File "D:\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\client\session.py", line 1370, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.NotFoundError: Key decoder_1/multi_rnn_cell/cell_0/lstm_cell/bias not found in checkpoint
[[node save/RestoreV2 (defined at \untitled\study\Example_4\model.py:201) ]]

Original stack trace for 'save/RestoreV2':
File "/untitled/study/Example_4/train.py", line 27, in
model.train(source_input, target_input, target_output, src_vocab_table, tgt_vocab_table, data.gen_batch)
File "\untitled\study\Example_4\model.py", line 201, in train
saver = tf.train.Saver(params, max_to_keep=10)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\training\saver.py", line 825, in init
self.build()
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\training\saver.py", line 837, in build
self._build(self._filename, build_save=True, build_restore=True)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\training\saver.py", line 875, in _build
build_restore=build_restore)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\training\saver.py", line 508, in _build_internal
restore_sequentially, reshape)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\training\saver.py", line 328, in _AddRestoreOps
restore_sequentially)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\training\saver.py", line 575, in bulk_restore
return io_ops.restore_v2(filename_tensor, names, slices, dtypes)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\ops\gen_io_ops.py", line 1779, in restore_v2
name=name)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 788, in _apply_op_helper
op_def=op_def)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\util\deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\framework\ops.py", line 3616, in create_op
op_def=op_def)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\framework\ops.py", line 2005, in init
self._traceback = tf_stack.extract_stack()

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "D:\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\training\saver.py", line 1296, in restore
names_to_keys = object_graph_key_mapping(save_path)
File "D:\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\training\saver.py", line 1614, in object_graph_key_mapping
object_graph_string = reader.get_tensor(trackable.OBJECT_GRAPH_PROTO_KEY)
File "D:\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 678, in get_tensor
return CheckpointReader_GetTensor(self, compat.as_bytes(tensor_str))
tensorflow.python.framework.errors_impl.NotFoundError: Key _CHECKPOINTABLE_OBJECT_GRAPH not found in checkpoint

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "D:/untitled/study/Example_4/train.py", line 27, in
model.train(source_input, target_input, target_output, src_vocab_table, tgt_vocab_table, data.gen_batch)
File "D:\untitled\study\Example_4\model.py", line 209, in train
saver.restore(sess, check_point)
File "D:\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\training\saver.py", line 1302, in restore
err, "a Variable name or other graph key that is missing")
tensorflow.python.framework.errors_impl.NotFoundError: Restoring from checkpoint failed. This is most likely due to a Variable name or other graph key that is missing from the checkpoint. Please ensure that you have not altered the graph expected based on the checkpoint. Original error:

Key decoder_1/multi_rnn_cell/cell_0/lstm_cell/bias not found in checkpoint
[[node save/RestoreV2 (defined at \untitled\study\Example_4\model.py:201) ]]

Original stack trace for 'save/RestoreV2':
File "/untitled/study/Example_4/train.py", line 27, in
model.train(source_input, target_input, target_output, src_vocab_table, tgt_vocab_table, data.gen_batch)
File "\untitled\study\Example_4\model.py", line 201, in train
saver = tf.train.Saver(params, max_to_keep=10)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\training\saver.py", line 825, in init
self.build()
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\training\saver.py", line 837, in build
self._build(self._filename, build_save=True, build_restore=True)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\training\saver.py", line 875, in _build
build_restore=build_restore)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\training\saver.py", line 508, in _build_internal
restore_sequentially, reshape)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\training\saver.py", line 328, in _AddRestoreOps
restore_sequentially)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\training\saver.py", line 575, in bulk_restore
return io_ops.restore_v2(filename_tensor, names, slices, dtypes)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\ops\gen_io_ops.py", line 1779, in restore_v2
name=name)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 788, in _apply_op_helper
op_def=op_def)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\util\deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\framework\ops.py", line 3616, in create_op
op_def=op_def)
File "\anaconda\envs\torchgpu\lib\site-packages\tensorflow\python\framework\ops.py", line 2005, in init
self._traceback = tf_stack.extract_stack()

BasicConvLSTM batch size can't be different between training and inference

Hi Wang,

Thanks for your sharing of peephole version ConvLSTM. However I found that the first dimension of peephole parameters 'w_ci', 'w_cf' and 'w_co' is related to batch size, which mades me unable to set different batch size during training and inference. Is it a bug or it has to be so?

Thank you so much.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.