keras

问题 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

问题 I have a Keras Sequential model taking inputs from csv files. When I run the model, its accuracy remains zero even after 20 epochs. I have gone through these two stackoverflow threads (zero-accuracy-training and why-is-the-accuracy-for-my-keras-model-always-0) but nothing solved my problem. As my model is binary classification, and I think it should not work like a regression model to make accuracy metric ineffective. Here is the Model def preprocess(*fields): return tf.stack(fields[:-1]), tf

问题 The Keras website has this article about exporting Keras models to core Tensorflow. However the step new_model = model_from_config(config) throws an error: Traceback (most recent call last): File "/home/hal9000/tf_serving_experiments/sndbx.py", line 38, in <module> new_model = model_from_config(config) File "/home/hal9000/keras2env/local/lib/python2.7/site-packages/keras/models.py", line 304, in model_from_config return layer_module.deserialize(config, custom_objects=custom_objects) File "

问题 I recently was reading a Pytorch code and came across loss.backward() and optimizer.step() functions, are there any equivalent of these using tensorflow/keras? 回答1: loss.backward() equivalent in tensorflow is tf.GradientTape() . TensorFlow provides the tf.GradientTape API for automatic differentiation - computing the gradient of a computation with respect to its input variables. Tensorflow "records" all operations executed inside the context of a tf.GradientTape onto a "tape". Tensorflow then

问题 I recently was reading a Pytorch code and came across loss.backward() and optimizer.step() functions, are there any equivalent of these using tensorflow/keras? 回答1: loss.backward() equivalent in tensorflow is tf.GradientTape() . TensorFlow provides the tf.GradientTape API for automatic differentiation - computing the gradient of a computation with respect to its input variables. Tensorflow "records" all operations executed inside the context of a tf.GradientTape onto a "tape". Tensorflow then

问题 I have a sequence prediction problem in which, given the last n items in a sequence I need to predict next item. I have more than 2 million sequences each with different timesteps ( length of sequence ), like some are just 5 and some are 50/60/100/200 upto 500. seq_inputs = [ ["AA1", "BB3", "CC4",…,"DD5"], #length/timeteps 5 ["FF1", "DD3", "FF6","KK8","AA5", "CC8",…, "AA2"] #length/timeteps 50 ["AA2", "CC8", "CC11","DD3", "FF6","AA1", "BB3",……,”DD11”]#length/timesteps 200 .. .. ] # there are

问题 I have a sequence prediction problem in which, given the last n items in a sequence I need to predict next item. I have more than 2 million sequences each with different timesteps ( length of sequence ), like some are just 5 and some are 50/60/100/200 upto 500. seq_inputs = [ ["AA1", "BB3", "CC4",…,"DD5"], #length/timeteps 5 ["FF1", "DD3", "FF6","KK8","AA5", "CC8",…, "AA2"] #length/timeteps 50 ["AA2", "CC8", "CC11","DD3", "FF6","AA1", "BB3",……,”DD11”]#length/timesteps 200 .. .. ] # there are

问题 I am new in R and trying keras in Rstudio . All the accuracy , loss interactive plots by running fit() are appearing in Viewer pane instead of Rmarkdown file. All other plots usually plot inside Rmarkdown files but not with keras. I have also checked Global settings in Rstudio Tools>Global Options>R Markdown>Show output preview in "Window" . How do I make them plot in Rmarkdown instead of Viewer Pane. How do I make this mandatory for all plots to create inside Rmarkdown files only and now in

问题 I am new in R and trying keras in Rstudio . All the accuracy , loss interactive plots by running fit() are appearing in Viewer pane instead of Rmarkdown file. All other plots usually plot inside Rmarkdown files but not with keras. I have also checked Global settings in Rstudio Tools>Global Options>R Markdown>Show output preview in "Window" . How do I make them plot in Rmarkdown instead of Viewer Pane. How do I make this mandatory for all plots to create inside Rmarkdown files only and now in

问题 I am new in R and trying keras in Rstudio . All the accuracy , loss interactive plots by running fit() are appearing in Viewer pane instead of Rmarkdown file. All other plots usually plot inside Rmarkdown files but not with keras. I have also checked Global settings in Rstudio Tools>Global Options>R Markdown>Show output preview in "Window" . How do I make them plot in Rmarkdown instead of Viewer Pane. How do I make this mandatory for all plots to create inside Rmarkdown files only and now in