how to see tensor value of a layer output in keras - tensorflow

Question

I have a Seq2Seq model. I am interested to print out the matrix value of the output of the encoder per iteration.
So for example as the dimension of the matrix in the encoder is (?,20) and the epoch =5 and in each epoch, there are 10 iteration,
I would like to see 10 matrix of the dimension (?,20) per epoch.
I have gone to several links as here but it still does not print out the value matrix.
With this code as mentioned in the aboved link:
import keras.backend as K
k_value = K.print_tensor(encoded)
print(k_value)
I got:
Tensor("Print:0", shape=(?, 20), dtype=float32)
Is there any straightforward way of showing the tensor value of each layer in Keras?
Update 1
by trying this code: K_value = K.eval(encoded) it raises this error:
Traceback (most recent call last):
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1278, in _do_call
return fn(*args)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1263, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1350, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'input' with dtype float and shape [?,45,50]
[[Node: input = Placeholder[dtype=DT_FLOAT, shape=[?,45,50], _device="/job:localhost/replica:0/task:0/device:GPU:0"]()]]
[[Node: encoder_lstm/add_16/_25 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_460_encoder_lstm/add_16", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/sgnbx/Downloads/projects/LSTM_autoencoder/justfun.py", line 121, in <module>
k_value = K.eval(encoded)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 671, in eval
return to_dense(x).eval(session=get_session())
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 680, in eval
return _eval_using_default_session(self, feed_dict, self.graph, session)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 4951, in _eval_using_default_session
return session.run(tensors, feed_dict)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 877, in run
run_metadata_ptr)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1100, in _run
feed_dict_tensor, options, run_metadata)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1272, in _do_run
run_metadata)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1291, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'input' with dtype float and shape [?,45,50]
[[Node: input = Placeholder[dtype=DT_FLOAT, shape=[?,45,50], _device="/job:localhost/replica:0/task:0/device:GPU:0"]()]]
[[Node: encoder_lstm/add_16/_25 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_460_encoder_lstm/add_16", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
Caused by op 'input', defined at:
File "/home/sgnbx/Downloads/projects/LSTM_autoencoder/justfun.py", line 113, in <module>
inputs = Input(shape=(SEQUENCE_LEN, EMBED_SIZE), name="input")
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/keras/engine/input_layer.py", line 177, in Input
input_tensor=tensor)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/keras/legacy/interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/keras/engine/input_layer.py", line 86, in __init__
name=self.name)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 515, in placeholder
x = tf.placeholder(dtype, shape=shape, name=name)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/tensorflow/python/ops/array_ops.py", line 1735, in placeholder
return gen_array_ops.placeholder(dtype=dtype, shape=shape, name=name)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/tensorflow/python/ops/gen_array_ops.py", line 4925, in placeholder
"Placeholder", dtype=dtype, shape=shape, name=name)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/tensorflow/python/util/deprecation.py", line 454, in new_func
return func(*args, **kwargs)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 3155, in create_op
op_def=op_def)
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1717, in __init__
self._traceback = tf_stack.extract_stack()
InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'input' with dtype float and shape [?,45,50]
[[Node: input = Placeholder[dtype=DT_FLOAT, shape=[?,45,50], _device="/job:localhost/replica:0/task:0/device:GPU:0"]()]]
[[Node: encoder_lstm/add_16/_25 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_460_encoder_lstm/add_16", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
Exception ignored in: <bound method BaseSession.__del__ of <tensorflow.python.client.session.Session object at 0x7fd900525c50>>
Traceback (most recent call last):
File "/home/sgnbx/anaconda3/envs/py3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 686, in __del__
TypeError: 'NoneType' object is not callable
Process finished with exit code 1

Answer 1

Very simple way to print a tensor :
from keras import backend as K
k_value = K.eval(tensor)
print(k_value)
UPDATE 1
Create a callback to print at the end of each epoch :
class callback(Callback):
def __init__(self, model, X_train):
self.model = model
self.x = X_train
def on_train_begin(self, logs={}):
return
def on_train_end(self, logs={}):
return
def on_epoch_begin(self, epoch, logs={}):
return
def on_epoch_end(self, epoch, logs={}):
inp = model.input # input placeholder
outputs = model.layers[N].output # get output of N's layer
functors = K.function([inp, K.learning_phase()], [outputs])
layer_outs = functors([self.x, 1.])
print('\r OUTPUT TENSOR : %s' % layer_outs)
return
def on_batch_begin(self, batch, logs={}):
return
def on_batch_end(self, batch, logs={}):
return
Call this function in your fit() method like that :
callbacks=[callback(model = model, X_train = X_train)])
Inspired from Keras, How to get the output of each layer?
Hope this will finally help you !