da73514fe9af58f35dc62a5c0c91ab60fd55f134,tensorforce/core/models/model.py,Model,api_act,#Model#,765

Before Change

            return tf.group(*assignments)

        with tf.control_dependencies(control_inputs=util.flatten(xs=actions)):
            reversed_variable_noise = self.cond(
                pred=skip_variable_noise, true_fn=no_variable_noise,
                false_fn=reverse_variable_noise
            )

        // Update states/internals/actions buffers
        def update_buffers():
            operations = list()
            buffer_index = self.buffer_index[parallel]
            for name in self.states_spec:
                operations.append(
                    self.states_buffer[name].scatter_nd_update(
                        indices=[(parallel, buffer_index)], updates=states[name]
                    )
                )
            for name in self.internals_spec:
                operations.append(
                    self.internals_buffer[name].scatter_nd_update(
                        indices=[(parallel, buffer_index)], updates=internals[name]
                    )
                )
            for name in self.actions_spec:
                operations.append(
                    self.actions_buffer[name].scatter_nd_update(
                        indices=[(parallel, buffer_index)], updates=actions[name]
                    )
                )

            // Increment buffer index
            with tf.control_dependencies(control_inputs=operations):
                one = tf.constant(value=1, dtype=util.tf_dtype(dtype="int"))
                incremented_buffer_index = self.buffer_index.scatter_nd_add(
                    indices=[(parallel,)], updates=[one]
                )

            with tf.control_dependencies(control_inputs=(incremented_buffer_index,)):
                return tf.no_op()

        with tf.control_dependencies(control_inputs=(reversed_variable_noise,)):
            updated_buffers = self.cond(
                pred=independent, true_fn=tf.no_op, false_fn=update_buffers
            )

After Change

                    assignments.append(variable.assign_sub(delta=noise, read_value=False))
                return tf.group(*assignments)

            reversed_variable_noise = self.cond(
                pred=skip_variable_noise, true_fn=no_variable_noise,
                false_fn=reverse_variable_noise
            )

        // Update states/internals/actions buffers
        with tf.control_dependencies(control_inputs=(reversed_variable_noise,)):

            def update_buffers():
                operations = list()
                buffer_index = self.buffer_index[parallel]
                for name in self.states_spec:
                    operations.append(
                        self.states_buffer[name].scatter_nd_update(
                            indices=[(parallel, buffer_index)], updates=states[name]
                        )
                    )
                for name in self.internals_spec:
                    operations.append(
                        self.internals_buffer[name].scatter_nd_update(
                            indices=[(parallel, buffer_index)], updates=internals[name]
                        )
                    )
                for name in self.actions_spec:
                    operations.append(
                        self.actions_buffer[name].scatter_nd_update(
                            indices=[(parallel, buffer_index)], updates=actions[name]
                        )
                    )

                // Increment buffer index
                with tf.control_dependencies(control_inputs=operations):
                    one = tf.constant(value=1, dtype=util.tf_dtype(dtype="int"))
                    incremented_buffer_index = self.buffer_index.scatter_nd_add(
                        indices=[(parallel,)], updates=[one]
                    )

                with tf.control_dependencies(control_inputs=(incremented_buffer_index,)):
                    return tf.no_op()

            updated_buffers = self.cond(
                pred=independent, true_fn=tf.no_op, false_fn=update_buffers
            )

        // Return timestep
        with tf.control_dependencies(control_inputs=(updated_buffers,)):
            // Function-level identity operation for retrieval (plus enforce dependency)
            for name, spec in self.actions_spec.items():
                actions[name] = util.identity_operation(

Instances