TypeError: ('Keyword argument not understood:', 'border_mode')

[namaa4555]

from keras.models import Sequential,Model
from keras.layers import Dense, Dropout, Flatten
from keras.layers import Conv2D,Activation,MaxPooling2D
from keras.utils import normalize
from keras.layers import Concatenate
from keras import Input
from keras.callbacks import ModelCheckpoint

input_shape=data.shape[1:] #50,50,1
inp=Input(shape=input_shape)
convs=[]

parrallel_kernels=[3,5,7]

for k in range(len(parrallel_kernels)):

conv = Conv2D(128, parrallel_kernels[k],border_mode='same',activation='relu',input_shape=input_shape,strides=1)(inp)
convs.append(conv)

out = Concatenate()(convs)
conv_model = Model(input=inp, output=out)

model = Sequential()
model.add(conv_model)

model.add(Conv2D(64,(3,3)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2,2)))

model.add(Conv2D(32,(3,3)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2,2)))

model.add(Flatten())
model.add(Dropout(0.5))
model.add(Dense(128,activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(64,activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(2,input_dim=128,activation='softmax'))
model.compile(loss='categorical_crossentropy',optimizer='adam',metrics=['accuracy'])

model.summary()

ihave the error

TypeError Traceback (most recent call last)
in
15 for k in range(len(parrallel_kernels)):
16
---> 17 conv = Conv2D(128, parrallel_kernels[k],border_mode='same',activation='relu',input_shape=input_shape,strides=1)(inp)
18 convs.append(conv)
19

~\anaconda3\lib\site-packages\tensorflow\python\keras\layers\convolutional.py in init(self, filters, kernel_size, strides, padding, data_format, dilation_rate, activation, use_bias, kernel_initializer, bias_initializer, kernel_regularizer, bias_regularizer, activity_regularizer, kernel_constraint, bias_constraint, **kwargs)
580 it will be channels_last.
581 dilation_rate: an integer or tuple/list of 2 integers, specifying the
--> 582 dilation rate to use for dilated convolution. Can be a single integer to
583 specify the same value for all spatial dimensions. Currently, specifying
584 any dilation_rate value != 1 is incompatible with specifying any stride

~\anaconda3\lib\site-packages\tensorflow\python\keras\layers\convolutional.py in init(self, rank, filters, kernel_size, strides, padding, data_format, dilation_rate, activation, use_bias, kernel_initializer, bias_initializer, kernel_regularizer, bias_regularizer, activity_regularizer, kernel_constraint, bias_constraint, trainable, name, **kwargs)
119 groups=1,
120 activation=None,
--> 121 use_bias=True,
122 kernel_initializer='glorot_uniform',
123 bias_initializer='zeros',

~\anaconda3\lib\site-packages\tensorflow\python\training\tracking\base.py in _method_wrapper(self, *args, **kwargs)
454 previous_value = getattr(self, "_self_setattr_tracking", True)
455 self._self_setattr_tracking = False # pylint: disable=protected-access
--> 456 try:
457 result = method(self, *args, **kwargs)
458 finally:

~\anaconda3\lib\site-packages\tensorflow\python\keras\engine\base_layer.py in init(self, trainable, name, dtype, dynamic, **kwargs)
292 # must_restore_from_config to return True; layers with this property must
293 # be restored into their actual objects (and will fail if the object is
--> 294 # not available to the restoration code).
295 _must_restore_from_config = False
296

~\anaconda3\lib\site-packages\tensorflow\python\keras\utils\generic_utils.py in validate_kwargs(kwargs, allowed_kwargs, error_message)
790
791
--> 792 def is_default(method):
793 """Check if a method is decorated with the default wrapper."""
794 return getattr(method, '_is_default', False)

TypeError: ('Keyword argument not understood:', 'border_mode')

[Anirudh Reddy]

border_mode is now called padding. as mentioned here.
keras-team/keras#1984 (comment)