def infer_shape(self, node, input_shapes):
V, W, b, d = node.inputs
V_shape, W_shape, b_shape, d_shape = input_shapes
dr = d[0]
dc = d[1]
dt = d[2]
batch_size = V_shape[0]
output_channels = W_shape[0]
vidHeight = V_shape[1]
filterHeight = W_shape[1]
vidWidth = V_shape[2]
filterWidth = W_shape[2]
vidDur = V_shape[3]
filterDur = W_shape[3]
output_height = T.floor((vidHeight - filterHeight) // dr) + 1
output_width = T.floor((vidWidth - filterWidth) // dc) + 1
output_dur = T.floor((vidDur - filterDur) // dt) + 1
rval = (batch_size, output_height, output_width, output_dur, output_channels )
return [rval]
def infer_shape(self, node, input_shapes):
V,W,b,d = node.inputs
V_shape, W_shape, b_shape, d_shape = input_shapes
dr = d[0]
dc = d[1]
dt = d[2]
batch_size = V_shape[0]
output_channels = W_shape[0]
vidHeight = V_shape[1]
filterHeight = W_shape[1]
vidWidth = V_shape[2]
filterWidth = W_shape[2]
vidDur = V_shape[3]
filterDur = W_shape[3]
output_height = T.floor((vidHeight - filterHeight) // dr) + 1
output_width = T.floor((vidWidth - filterWidth) // dc) + 1
output_dur = T.floor((vidDur - filterDur) // dt) + 1
rval = (batch_size, output_height, output_width, output_dur, output_channels )
return [rval]
