##############################################################################bl
# MIT License
#
# Copyright (c) 2021 - 2023 Advanced Micro Devices, Inc. All Rights Reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
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# The above copyright notice and this permission notice shall be included in all
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
##############################################################################el

#
# Define all common data storage classes,
# predifned dict and global functions.
#

import pandas as pd
from typing import Dict, List, Mapping, Generator
from dataclasses import dataclass, field
from collections import OrderedDict


@dataclass
class ArchConfig:
    # [id: panel_config] pairs
    panel_configs: OrderedDict = field(default=dict)

    # [id: df] pairs
    dfs: Dict[int, pd.DataFrame] = field(default_factory=dict)

    # NB:
    #  dfs_type should be a meta info embeded into df.
    #  pandas.DataFrame.attrs is experimental and may change without warning.
    #  So do it as below for now.

    # [id: df_type] pairs
    dfs_type: Dict[int, str] = field(default_factory=dict)

    # [Index: Metric name] pairs
    metric_list: Dict[str, str] = field(default_factory=dict)

    # [Metric name: Counters] pairs
    metric_counters: Dict[str, list] = field(default_factory=dict)


@dataclass
class Workload:
    sys_info: pd.DataFrame = None
    soc_spec: dict = None  # TODO: might move it to ArchConfig
    raw_pmc: pd.DataFrame = None
    dfs: Dict[int, pd.DataFrame] = field(default_factory=dict)
    dfs_type: Dict[int, str] = field(default_factory=dict)
    filter_kernel_ids: List[int] = field(default_factory=list)
    filter_gpu_ids: List[int] = field(default_factory=list)
    filter_dispatch_ids: List[int] = field(default_factory=list)
    avail_ips: List[int] = field(default_factory=list)


# Metrics will be calculated ONLY when the header(key) is in below list
supported_field = [
    "Value",
    "Minimum",
    "Maximum",
    "Average",
    "Median",
    "Min",
    "Max",
    "Avg",
    "PoP",
    "Peak",
    "Count",
    "Mean",
    "Pct",
    "Std Dev",
    "Q1",
    "Q3",
    "Expression",
    # Special keywords for L2 channel
    "Channel",
    "L2 Cache Hit Rate",
    "Requests",
    "L1-L2 Read",
    "L1-L2 Write",
    "L1-L2 Atomic",
    "L2-EA Read",
    "L2-EA Write",
    "L2-EA Atomic",
    "L2-EA Read Latency",
    "L2-EA Write Latency",
    "L2-EA Atomic Latency",
    "L2-EA Read Stall - IO",
    "L2-EA Read Stall - GMI",
    "L2-EA Read Stall - DRAM",
    "L2-EA Write Stall - IO",
    "L2-EA Write Stall - GMI",
    "L2-EA Write Stall - DRAM",
    "L2-EA Write Stall - Starve",
]

# The prefix of raw pmc_perf.csv
pmc_perf_file_prefix = "pmc_perf"