def _reset_parameters(self):
xavier_uniform_fan_in_(self.in_proj.weight)
xavier_uniform_fan_in_(self.out_proj.weight)
if self.in_proj.bias is not None:
nn.init.zeros_(self.in_proj.bias)
if self.out_proj.bias is not None:
nn.init.zeros_(self.out_proj.bias)
def _reset_parameters(self):
if hasattr(self, "bow_proj_layer"):
xavier_uniform_fan_in_(self.bow_proj_layer.weight)
nn.init.zeros_(self.bow_proj_layer.bias)
xavier_uniform_fan_in_(self.emb2states_fwd.weight)
xavier_uniform_fan_in_(self.emb2states_bwd.weight)
nn.init.zeros_(self.emb2states_fwd.bias)
nn.init.zeros_(self.emb2states_bwd.bias)
if hasattr(self, "fwd_out_proj"):
xavier_uniform_fan_in_(self.fwd_out_proj.weight)
if hasattr(self, "bwd_out_proj"):
xavier_uniform_fan_in_(self.bwd_out_proj.weight)
def _reset_parameters(self):
xavier_uniform_fan_in_(self.linear.weight, activation="tanh")
def _reset_parameters(self):
xavier_uniform_fan_in_(self.hidden2latent.weight)
nn.init.zeros_(self.hidden2latent.bias)
def _reset_parameters(self):
xavier_uniform_fan_in_(self.in_proj.weight)
nn.init.zeros_(self.in_proj.bias)
xavier_uniform_fan_in_(self.out_proj.weight, activation="relu")
nn.init.zeros_(self.out_proj.bias)
def _reset_parameters(self):
xavier_uniform_fan_in_(self.in_proj.weight)
xavier_uniform_fan_in_(self.out_proj.weight, activation="tanh")
def _reset_parameters(self):
xavier_uniform_fan_in_(self.input_transform.weight)
nn.init.orthogonal_(self.states_transform.weight)
if self.use_bias:
nn.init.zeros_(self.input_transform.bias)
nn.init.zeros_(self.states_transform.bias)
def _reset_parameters(self):
xavier_uniform_fan_in_(self.weight_ih)
nn.init.orthogonal_(self.weight_hh)
if self.bias:
nn.init.zeros_(self.bias_ih)
nn.init.zeros_(self.bias_hh)
def _reset_parameters(self):
if not self.opts.weight_typing:
xavier_uniform_fan_in_(self.out_proj.weight)
def _reset_parameters(self):
if hasattr(self, "bow_proj_layer"):
xavier_uniform_fan_in_(self.bow_proj_layer.weight)
nn.init.zeros_(self.bow_proj_layer.bias)
if not self.opts.weight_typing:
xavier_uniform_fan_in_(self.out_proj.weight)
def _reset_parameters(self):
if self.embedding_dim != self.latent_dim:
xavier_uniform_fan_in_(self.latent2emb.weight)
nn.init.zeros_(self.latent2emb.bias)
def _reset_parameters(self):
if self.empty_base:
return
if isinstance(self.out_proj, nn.Linear):
xavier_uniform_fan_in_(self.out_proj.weight)