Method compile

python/paddle/base/compiler.py:1154–1285

This interface is used to compile the input Program to a program to run the model on the ipu. Args: feed_list(list): This parameter represents the input Tensors of the model. fetch_list(list): This parameter represents the Tensors that need to be re

(self, feed_list: list[str], fetch_list: list[str])

        self._backend = core.IpuBackend.get_instance()

    def compile(self, feed_list: list[str], fetch_list: list[str]) -> Program:
        """
        This interface is used to compile the input Program to a program
        to run the model on the ipu.

        Args:
            feed_list(list): This parameter represents the input Tensors of the model.

            fetch_list(list): This parameter represents the Tensors that need to be returned
                after the model.

        Returns:
            Program

        Example:
            .. code-block:: pycon

                >>> # doctest: +REQUIRES(env:IPU)

                >>> import paddle
                >>> import paddle.static as static

                >>> paddle.enable_static()

                >>> a = static.data(name='data', shape=[None, 1], dtype='int32')
                >>> b = a + 1
                >>> main_prog = static.default_main_program()

                >>> ipu_strategy = static.IpuStrategy()
                >>> ipu_strategy.set_graph_config(num_ipus=1, is_training=True, micro_batch_size=1)
                >>> ipu_strategy.set_pipelining_config(
                ...     enable_pipelining=False,
                ...     batches_per_step=1,
                ...     enable_gradient_accumulation=False,
                ...     accumulation_factor=1,
                ... )
                >>> ipu_strategy.set_precision_config(enable_fp16=False)

                >>> program = static.IpuCompiledProgram(
                ...     main_prog,
                ...     ipu_strategy=ipu_strategy,
                ... ).compile([a.name], [b.name])
        """
        self._backend.set_scope(self._scope)
        self._backend.set_ipu_strategy(self._ipu_strategy._ipu_strategy)

        # feed and fetch doesn't have corresponding popart op, so we rm both here
        global_block = self._program.global_block()
        need_to_remove_op_index = []
        for i, op in enumerate(global_block.ops):
            op.desc.set_is_target(False)
            if op.type == 'feed' or op.type == 'fetch':
                need_to_remove_op_index.append(i)

        for index in need_to_remove_op_index[::-1]:
            global_block._remove_op(index)

        for var in ['feed', 'fetch']: