I am working in python and tensor flow but I miss 'units' argument and I do not know how to solve it, It looks like your post is mostly code; please add some more details.It looks like your post is mostly code; please add some more details.
here the code
def createModel():
model = Sequential()
# first set of CONV => RELU => MAX POOL layers
model.add(Conv2D(32, (3, 3), padding='same', activation='relu', input_shape=inputShape))
model.add(Conv2D(32, (3, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))
model.add(Conv2D(64, (3, 3), padding='same', activation='relu'))
model.add(Conv2D(64, (3, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))
model.add(Conv2D(64, (3, 3), padding='same', activation='relu'))
model.add(Conv2D(64, (3, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))
model.add(Flatten())
model.add(Dense(512, activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(output_dim=NUM_CLASSES, activation='softmax'))
# returns our fully constructed deep learning + Keras image classifier
opt = Adam(lr=INIT_LR, decay=INIT_LR / EPOCHS)
# use binary_crossentropy if there are two classes
model.compile(loss="categorical_crossentropy", optimizer=opt, metrics=["accuracy"])
return model
print("Reshaping trainX at..."+ str(datetime.now()))
#print(trainX.sample())
print(type(trainX)) # <class 'pandas.core.series.Series'>
print(trainX.shape) # (750,)
from numpy import zeros
Xtrain = np.zeros([trainX.shape[0],HEIGHT, WIDTH, DEPTH])
for i in range(trainX.shape[0]): # 0 to traindf Size -1
Xtrain[i] = trainX[i]
print(Xtrain.shape) # (750,128,128,3)
print("Reshaped trainX at..."+ str(datetime.now()))
print("Reshaping valX at..."+ str(datetime.now()))
print(type(valX)) # <class 'pandas.core.series.Series'>
print(valX.shape) # (250,)
from numpy import zeros
Xval = np.zeros([valX.shape[0],HEIGHT, WIDTH, DEPTH])
for i in range(valX.shape[0]): # 0 to traindf Size -1
Xval[i] = valX[i]
print(Xval.shape) # (250,128,128,3)
print("Reshaped valX at..."+ str(datetime.now()))
# initialize the model
print("compiling model...")
sys.stdout.flush()
model = createModel()
# print the summary of model
from keras.utils import print_summary
print_summary(model, line_length=None, positions=None, print_fn=None)
# add some visualization
from IPython.display import SVG
from keras.utils.vis_utils import model_to_dot
SVG(model_to_dot(model).create(prog='dot', format='svg'))
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