oswaldoludwig / adversarial-learning-for-generative-conversational-agents Goto Github PK

Traceback (most recent call last):
File "conversation_GAN.py", line 136, in
input_context = Input(shape=(maxlen_input,), dtype='int32', name='the context text')
File "/home/bala/.local/lib/python2.7/site-packages/keras/engine/input_layer.py", line 176, in Input
input_tensor=tensor)
File "/home/bala/.local/lib/python2.7/site-packages/keras/legacy/interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "/home/bala/.local/lib/python2.7/site-packages/keras/engine/input_layer.py", line 85, in init
name=self.name)
File "/home/bala/.local/lib/python2.7/site-packages/keras/backend/tensorflow_backend.py", line 514, in placeholder
x = tf.placeholder(dtype, shape=shape, name=name)
File "/home/bala/.local/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.py", line 1808, in placeholder
return gen_array_ops.placeholder(dtype=dtype, shape=shape, name=name)
File "/home/bala/.local/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.py", line 4848, in placeholder
"Placeholder", dtype=dtype, shape=shape, name=name)
File "/home/bala/.local/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 394, in _apply_op_helper
with g.as_default(), ops.name_scope(name) as scope:
File "/home/bala/.local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 5982, in enter
return self._name_scope.enter()
File "/usr/lib/python2.7/contextlib.py", line 17, in enter
return self.gen.next()
File "/home/bala/.local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 4105, in name_scope
raise ValueError("'%s' is not a valid scope name" % name)
ValueError: 'the context text' is not a valid scope name

Every time I tried conversation_GAN.py, I got warning message "2021-06-13 08:20:38.760895: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)"

2021-06-13 08:20:18.974838: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
Starting the model...
2021-06-13 08:20:27.346569: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-06-13 08:20:27.348320: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
2021-06-13 08:20:28.657984: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce GTX 1660 Ti computeCapability: 7.5
coreClock: 1.59GHz coreCount: 24 deviceMemorySize: 6.00GiB deviceMemoryBandwidth: 268.26GiB/s
2021-06-13 08:20:28.658324: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-06-13 08:20:28.678067: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-06-13 08:20:28.678321: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-06-13 08:20:28.688924: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-06-13 08:20:28.691826: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-06-13 08:20:28.694202: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cusolver64_10.dll'; dlerror: cusolver64_10.dll not found
2021-06-13 08:20:28.704387: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-06-13 08:20:28.706130: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-06-13 08:20:28.706359: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1757] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
2021-06-13 08:20:28.708451: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-06-13 08:20:28.711031: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-06-13 08:20:28.713796: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]
2021-06-13 08:20:28.715081: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set

CHAT:

computer: hi ! please type your name.

user: jack
computer: hi , jack ! My name is john.

user: hello john
2021-06-13 08:20:38.760895: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)

computer: good morning . can i help you ?
user: can you help me cleaning my room?

computer: yes , please . it is not dirty .
user:

I threw this code together which launches the chatterbot code directly against your trained model.
pip install git+git://github.com/gunthercox/ChatterBot.git

https://gist.github.com/johndpope/b0d9a025c6e54dc1e07ab6100c34a24a

the results were quite bad.

there's a bunch of yml files in chatterbot which if I get time will attempt to glue together - but it would be good to be able to have an api into this architecture where it could be corrected...or maybe that exists in codebase?

I understand this repo is to showcase whitepaper research - but wondered if you have ideas to take ai bots to another level. If you were to step back - and look at higher level of what could be achieved with blending technologies.

off the back of an envelope - some thoughts of mine
eg. by doing entity detection on sentence / have these carry forward
memory of stuff (I guess this opens up problems like microsoft's disastrous tai tai twitter bot)
eg. use elmo for understanding context of words
wikidata -> don't stop at entity detection / go beyond to understand meaning sentence.
use hybrid code network / action templates
Commonsense Knowledge

what do you see as the biggest challenge that needs solving?

I am trying to create weight file for my data. Model is giving gibberish responses.

Could you please list versions of the packages that you use in this project? I saw in another issue that it requires Python 2, but what about other stuff (e.g., Keras)?

File "conversation_GAN.py", line 96
if raw_word[-1] <> '!' and raw_word[-1] <> '?' and raw_word[-1] <> '.' and raw_word[-2:] <> '! ' and raw_word[-2:] <> '? ' and raw_word[-2:] <> '. ':
^
SyntaxError: invalid syntax