#!/usr/bin/env python3
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.

import argparse
import collections
import subprocess
import sys
import os


def parse_args():
    parser = argparse.ArgumentParser(description="Runs a BERT batch size test.")
    parser.add_argument("--binary_dir", required=True, help="Path to the ORT binary directory.")
    parser.add_argument("--model_root", required=True, help="Path to the model root directory.")
    parser.add_argument(
        "--gpu_sku",
        choices=["V100_16G", "MI100_32G"],
        default="V100_16G",
        required=False,
        help="GPU model (e.g. V100_16G, MI100_32G).",
    )
    return parser.parse_args()


def main():
    args = parse_args()

    Config = collections.namedtuple(
        "Config",
        [
            "enable_mixed_precision",
            "sequence_length",
            "max_batch_size",
            "max_predictions_per_seq",
            "additional_options",
        ],
    )

    configs = {}
    configs["V100_16G"] = [
        Config(True, 128, 76, 20, ""),
        Config(True, 512, 11, 80, ""),
        Config(False, 128, 39, 20, ""),
        Config(False, 512, 6, 80, ""),
        # BertLarge Phase 1 recompute
        Config(True, 128, 91, 20, "--gelu_recompute"),
        Config(True, 128, 83, 20, "--attn_dropout_recompute"),
        Config(True, 128, 344, 20, "--transformer_layer_recompute"),
        # BertLarge Phase 2 recompute
        Config(True, 512, 12, 80, "--gelu_recompute"),
        Config(True, 512, 14, 80, "--attn_dropout_recompute"),
        Config(True, 512, 50, 80, "--transformer_layer_recompute"),
    ]

    configs["MI100_32G"] = [
        Config(True, 128, 192, 20, ""),
        Config(True, 512, 26, 80, ""),
        Config(False, 128, 108, 20, ""),
        Config(False, 512, 16, 80, ""),
    ]

    # run BERT training
    for config in configs[args.gpu_sku]:
        print(
            "##### testing name - {}-{} #####".format(
                "fp16" if config.enable_mixed_precision else "fp32", config.sequence_length
            )
        )
        cmds = [
            os.path.join(args.binary_dir, "onnxruntime_training_bert"),
            "--model_name",
            os.path.join(
                args.model_root,
                "nv/bert-large/bert-large-uncased_L_24_H_1024_A_16_V_30528_S_512_Dp_0.1_optimized_layer_norm_opset12",
            ),
            "--train_batch_size",
            str(config.max_batch_size),
            "--mode",
            "perf",
            "--max_seq_length",
            str(config.sequence_length),
            "--num_train_steps",
            "10",
            "--display_loss_steps",
            "5",
            "--optimizer",
            "adam",
            "--learning_rate",
            "5e-4",
            "--warmup_ratio",
            "0.1",
            "--warmup_mode",
            "Linear",
            "--gradient_accumulation_steps",
            "1",
            "--max_predictions_per_seq=20",
            "--allreduce_in_fp16",
            "--lambda",
            "0",
            "--use_nccl",
            "--seed",
            "42",
            "--enable_grad_norm_clip=false",
            config.additional_options,
        ]

        if config.enable_mixed_precision:
            cmds.append("--use_mixed_precision"),

        subprocess.run(cmds, timeout=120).check_returncode()

    return 0


if __name__ == "__main__":
    sys.exit(main())
