class_docstr: Implementation of Spatio-Temporal Graph Convolutional Networks
docstr: Spatio-Temporal convolution block
docstr_tok: ["Spatio-Temporal","convolution","block"]
code: def st_conv_block(
      self, x, Ks, Kt, channels, name, keep_prob, act_func="GLU"
  ):
      """Spatio-Temporal convolution block"""
      c_si, c_t, c_oo = channels
  
      x_s = self.temporal_conv_layer(
          x, Kt, c_si, c_t, "%s_tconv_in" % name, act_func=act_func
      )
      x_t = self.spatio_conv_layer(x_s, Ks, c_t, c_t, "%s_sonv" % name)
      x_o = self.temporal_conv_layer(
          x_t, Kt, c_t, c_oo, "%s_tconv_out" % name
      )
  
      x_ln = fl.layer_norm(x_o)
      return fl.dropout(x_ln, dropout_prob=(1.0 - keep_prob))
  
file_path: PGL/legacy/examples/stgcn/models/model.py
imports: import numpy
  import paddle.fluid
  import paddle.fluid.layers
  import pgl
label_desc: Use image node_id 3 for calling the STGCNModel obj's underlying member method code with example usage: obj.st_conv_block(x, Ks, Kt, channels, name, keep_prob, act_func) and returns: fl