def write_results()

in ignite/handlers/time_profilers.py [0:0]


    def write_results(self, output_path: str) -> None:
        """
        Method to store the unaggregated profiling results to a csv file

        Args:
            output_path: file output path containing a filename

        .. code-block:: python

            profiler.write_results('path_to_dir/awesome_filename.csv')

        Examples:
            .. code-block:: text

                -----------------------------------------------------------------
                epoch iteration processing_stats dataflow_stats Event_STARTED ...
                1.0     1.0        0.00003         0.252387        0.125676
                1.0     2.0        0.00029         0.252342        0.125123

        """
        try:
            import pandas as pd
        except ImportError:
            raise RuntimeError("Need pandas to write results as files")

        iters_per_epoch = self.total_num_iters // self.max_epochs

        epochs = torch.arange(self.max_epochs, dtype=torch.float32).repeat_interleave(iters_per_epoch) + 1
        iterations = torch.arange(self.total_num_iters, dtype=torch.float32) + 1
        processing_stats = self.processing_times
        dataflow_stats = self.dataflow_times

        event_started = self.event_handlers_times[Events.STARTED].repeat_interleave(self.total_num_iters)
        event_completed = self.event_handlers_times[Events.COMPLETED].repeat_interleave(self.total_num_iters)
        event_epoch_started = self.event_handlers_times[Events.EPOCH_STARTED].repeat_interleave(iters_per_epoch)
        event_epoch_completed = self.event_handlers_times[Events.EPOCH_COMPLETED].repeat_interleave(iters_per_epoch)

        event_iter_started = self.event_handlers_times[Events.ITERATION_STARTED]
        event_iter_completed = self.event_handlers_times[Events.ITERATION_COMPLETED]
        event_batch_started = self.event_handlers_times[Events.GET_BATCH_STARTED]
        event_batch_completed = self.event_handlers_times[Events.GET_BATCH_COMPLETED]

        results_dump = torch.stack(
            [
                epochs,
                iterations,
                processing_stats,
                dataflow_stats,
                event_started,
                event_completed,
                event_epoch_started,
                event_epoch_completed,
                event_iter_started,
                event_iter_completed,
                event_batch_started,
                event_batch_completed,
            ],
            dim=1,
        ).numpy()

        results_df = pd.DataFrame(
            data=results_dump,
            columns=[
                "epoch",
                "iteration",
                "processing_stats",
                "dataflow_stats",
                "Event_STARTED",
                "Event_COMPLETED",
                "Event_EPOCH_STARTED",
                "Event_EPOCH_COMPLETED",
                "Event_ITERATION_STARTED",
                "Event_ITERATION_COMPLETED",
                "Event_GET_BATCH_STARTED",
                "Event_GET_BATCH_COMPLETED",
            ],
        )
        results_df.to_csv(output_path, index=False)