Strided 2-D convolution with 'SAME' padding. When stride > 1, then we do explicit zero-padding, followed by conv2d with 'VALID' padding. Note that net = conv2d_same(inputs, num_outputs, 3, stride=stride) is equivalent to net = slim.conv2d(inputs, num_outputs, 3, stride=1, padd
(inputs, num_outputs, kernel_size, stride, rate=1, scope=None)
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