Failing to run a very simple Keras example

idata · ‎08-02-2018

Hi,

I'm moving the first steps in deep learning with Movidius stick, and I'm stuck in this very simple problem..

I have this very simple code in Keras:

import numpy as np

np.random.seed(123) # for reproducibility

from keras.models import Sequential

from keras.layers import Dense, Dropout, Activation, Flatten

from keras.layers import Convolution2D, MaxPooling2D

from keras.utils import np_utils

from keras.datasets import mnist

4. Load pre-shuffled MNIST data into train and test sets

(X_train, y_train), (X_test, y_test) = mnist.load_data()

5. Preprocess input data

X_train = X_train.reshape(X_train.shape[0], 28, 28, 1)

X_test = X_test.reshape(X_test.shape[0], 28, 28, 1)

X_train = X_train.astype('float32')

X_test = X_test.astype('float32')

X_train /= 255

X_test /= 255

6. Preprocess class labels

Y_train = np_utils.to_categorical(y_train, 10)

Y_test = np_utils.to_categorical(y_test, 10)

7. Define model architecture

model = Sequential()

model.add(Convolution2D(32, 3, 3, activation='relu', input_shape=(28,28,1), name="input"))

model.add(Convolution2D(32, 3, 3, activation='relu'))

model.add(MaxPooling2D(pool_size=(2,2)))

model.add(Dropout(0.25))

model.add(Flatten())

model.add(Dense(128, activation='relu'))

model.add(Dropout(0.5))

model.add(Dense(10, activation='softmax', name="output"))

8. Compile model

model.compile(loss='categorical_crossentropy',

optimizer='adam',

metrics=['accuracy'])

9. Fit model on training data

model.fit(X_train, Y_train,

batch_size=32, epochs=1, verbose=1)

10. Evaluate model on test data

score = model.evaluate(X_test, Y_test, verbose=0)

model_json = model.to_json()

with open("model.json", "w") as json_file:

json_file.write(model_json)

model.save_weights("model.h5")

I'm trying to generate a graph file using this tool: https://github.com/ardamavi/Intel-Movidius-NCS-Keras

But when it run mvNCCompile I get this error: KeyError: "The name 'input:0' refers to a Tensor which does not exist. The operation, 'input', does not exist in the graph."

Can you help me?

Thank you

idata · ‎08-02-2018

Sorry for my ignorance, I solved.. I just turned the model into functional keras mode and removed Dropouts layers.