pytorch equivalent of Conv2D in tenserflow with stride of 2 and padding of (1,1)
I have conv1 = nn.Conv2d(3, 16, 3,stride= 2, padding = 1, bias=True, groups=1) . i need its corresponding api in tf.keras.layers.Conv2D.
Can anyone help me out
PS : Here i have a stride of 2

I have found the solution , hope this might be help full to others as well  . As it was difficult to match padding in torch and padding in keras with stride = 2
X = Input(shape = (10,10,3))
X1 = ZeroPadding2D(padding=(1,1), input_shape=(10, 10, 3), data_format=&quot;channels_last&quot;)(X)
conv1 = Conv2D(16, 3,  padding = 'valid', strides = (2,2))(X1)

