def conv_decoder_infer(self):
maximum_iterations = self.params["max_decode_length"]
self.init_params_in_loop()
tf.get_variable_scope().reuse_variables()
outputs, final_state = dynamic_decode(
decoder=self,
output_time_major=True,
impute_finished=False,
maximum_iterations=maximum_iterations)
return outputs, final_state
def conv_decoder_infer(self):
maximum_iterations = self.params["max_decode_length"]
self.init_params_in_loop()
tf.get_variable_scope().reuse_variables()
outputs, final_state = dynamic_decode(
decoder=self,
output_time_major=True,
impute_finished=False,
maximum_iterations=maximum_iterations)
return outputs, final_state
def _build(self, initial_state, helper):
if not self.initial_state:
self._setup(initial_state, helper)
maximum_iterations = None
if self.mode == tf.contrib.learn.ModeKeys.INFER:
maximum_iterations = self.params["max_decode_length"]
outputs, final_state = dynamic_decode(
decoder=self,
output_time_major=True,
impute_finished=False,
maximum_iterations=maximum_iterations)
return self.finalize(outputs, final_state)
def _build(self, initial_state, helper):
if not self.initial_state:
self._setup(initial_state, helper)
scope = tf.get_variable_scope()
scope.set_initializer(
tf.random_uniform_initializer(-self.params["init_scale"],
self.params["init_scale"]))
maximum_iterations = None
if self.mode == tf.contrib.learn.ModeKeys.INFER:
maximum_iterations = self.params["max_decode_length"]
outputs, final_state = dynamic_decode(
decoder=self,
output_time_major=True,
impute_finished=False,
maximum_iterations=maximum_iterations)
return self.finalize(outputs, final_state)
def _build(self, initial_state, helper):
if not self.initial_state:
self._setup(initial_state, helper)
scope = tf.get_variable_scope()
scope.set_initializer(tf.random_uniform_initializer(
-self.params["init_scale"],
self.params["init_scale"]))
maximum_iterations = None
if self.mode == tf.contrib.learn.ModeKeys.INFER:
maximum_iterations = self.params["max_decode_length"]
outputs, final_state = dynamic_decode(
decoder=self,
output_time_major=True,
impute_finished=False,
maximum_iterations=maximum_iterations)
return self.finalize(outputs, final_state)
