我有一个Seq2Seq模型。我有兴趣打印出每次迭代编码器输出的矩阵值。
例如，由于encoder中矩阵的维数(?,20)，epoch =5和每个纪元中，都有10迭代， 我想看到10每epoch的维度(?,20)矩阵.
我已经转到了此处的几个链接，但它仍然没有打印出价值矩阵。 使用上述链接中提到的此代码：
import keras.backend as K
k_value = K.print_tensor(encoded)
print(k_value)
我得到了：
Tensor("Print:0", shape=(?, 20), dtype=float32)
有没有直接的方法可以在 Keras 中显示每层的张量值？
更新 1
通过尝试以下代码：K_value = K.eval(encoded)引发此错误：
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
打印张量的非常简单的方法：
from keras import backend as K
k_value = K.eval(tensor)
print(k_value)
更新 1
创建一个回调以在每个纪元结束时打印：
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
在 fit() 方法中调用此函数，如下所示：
callbacks=[callback(model = model, X_train = X_train)])
灵感来自 Keras，如何获取每一层的输出？
希望这最终能帮助你！