# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.

""" Utilities for operating with dicts and lists. """

import torch

from collections import defaultdict
from typing import Callable, Tuple, Optional, Iterable, Union, Any


def extract_matching_values(x: Union[dict, list], predicate: Callable) -> Tuple[Union[dict, list], Union[dict, list]]:
    """ Return matching and nonmatching values. Keeps hierarchy. """
    if isinstance(x, dict):
        matching_vals = {}
        nonmatching_vals = {}
        for k, v in x.items():
            if isinstance(v, (list, dict)):
                match, nonmatch = extract_matching_values(v, predicate)
                if match:
                    matching_vals[k] = match
                if nonmatch:
                    nonmatching_vals[k] = nonmatch
            elif predicate(v):
                matching_vals[k] = v
            else:
                nonmatching_vals[k] = v
    else:
        assert isinstance(x, list)
        matching_vals = []
        nonmatching_vals = []
        for v in x:
            if isinstance(v, (list, dict)) and v:
                match, nonmatch = extract_matching_values(v, predicate)
                if match:
                    matching_vals.append(match)
                if nonmatch:
                    nonmatching_vals.append(nonmatch)
            elif predicate(v):
                matching_vals.append(v)
            else:
                nonmatching_vals.append(v)
    return matching_vals, nonmatching_vals


def diff(x1: Any, x2: Any, prefix: Tuple = ()) -> Tuple[list, list, list]:
    mismatch = []
    if isinstance(x1, dict) and isinstance(x2, dict):
        only_left = [prefix + (k,) for k in x1.keys() - x2.keys()]
        only_right = [prefix + (k,) for k in x2.keys() - x1.keys()]
        for k in x2.keys() & x1.keys():
            _left, _right, _mismatch = diff(x1[k], x2[k], prefix + (k,))
            only_left.extend(_left)
            only_right.extend(_right)
            mismatch.extend(_mismatch)
    elif isinstance(x1, list) and isinstance(x2, list):
        only_left = list(range(len(x1) - 1, len(x2) - 1, -1))
        only_right = list(range(len(x1) - 1, len(x2) - 1, -1))
        for i, (v1, v2) in enumerate(zip(x1, x2)):
            _left, _right, _mismatch = diff(v1, v2, prefix + (i,))
            only_left.extend(_left)
            only_right.extend(_right)
            mismatch.extend(_mismatch)
    else:
        only_left = []
        only_right = []
        if isinstance(x1, torch.Tensor) and isinstance(x2, torch.Tensor):
            _is_mismatch = not torch.all(x1 == x2)
        else:
            try:
                _is_mismatch = bool(x1 != x2)
            except RuntimeError:
                _is_mismatch = True

        if _is_mismatch:
            x1_str = str(x1) if isinstance(x1, (int, float)) else type(x1)
            x2_str = str(x2) if isinstance(x2, (int, float)) else type(x2)
            mismatch.append((prefix, x1_str, x2_str))

    return only_left, only_right, mismatch


def inspect_types(x: Any, prefix: Tuple = (), indent: int = 4):
    print_indent = lambda: print(' ' * indent * len(prefix), end='')
    if isinstance(x, dict):
        print()
        for k, v in x.items():
            print_indent()
            print(f'> {k}: ', end='')
            inspect_types(v, prefix + (k,), indent)
    elif isinstance(x, list):
        print()
        for i, v in enumerate(x):
            print_indent()
            print(f'- {i}: ', end='')
            inspect_types(v, prefix + (i,), indent)
    else:
        if isinstance(x, torch.Tensor):
            print(f'Tensor of shape {x.shape}')
        else:
            try:
                x_str = str(x)
            except:
                x_str = '<no string repr>'
            if len(x_str) > 30:
                x_str = x_str[:30] + '... (truncated)'
            print(f'[{type(x)}]: {x_str}')


def inspect_types(x: Any, prefix: Tuple = (), indent: int = 4):
    print_indent = lambda: print(' ' * indent * len(prefix), end='')
    if isinstance(x, dict):
        print()
        for k, v in x.items():
            print_indent()
            print(f'> {k}: ', end='')
            inspect_types(v, prefix + (k,), indent)
    elif isinstance(x, list):
        print()
        for i, v in enumerate(x):
            print_indent()
            print(f'- {i}: ', end='')
            inspect_types(v, prefix + (i,), indent)
    else:
        if isinstance(x, torch.Tensor):
            print(f'Tensor of shape {x.shape}')
        else:
            try:
                x_str = str(x)
            except:
                x_str = '<no string repr>'
            if len(x_str) > 30:
                x_str = x_str[:30] + '... (truncated)'
            print(f'[{type(x)}]: {x_str}')


def nested_values(x: Union[dict, list]):
    x_iter = x.values() if isinstance(x, dict) else x
    for v in x_iter:
        if isinstance(v, (dict, list)):
            yield from nested_values(v)
        else:
            yield v


def nested_items_iter(d: dict):
    for k, v in d.items():
        if isinstance(v, dict):
            yield from nested_items_iter(v)
        else:
            yield d, k, v


def dict_map(f: Callable, d: dict):
    for sub_d, k, v in nested_items_iter(d):
        sub_d[k] = f(v)


def dict_map_with_key(f: Callable, d: dict):
    for sub_d, k, v in nested_items_iter(d):
        sub_d[k] = f(k, v)


def dict_list_map_inplace(f: Callable, x: Union[dict, list]):
    if isinstance(x, dict):
        for k, v in x.items():
            x[k] = dict_list_map_inplace(f, v)
    elif isinstance(x, list):
        x[:] = (dict_list_map_inplace(f, v) for v in x)
    else:
        return f(x)
    return x


def dict_list_map_outplace(f: Callable, x: Union[dict, list]):
    if isinstance(x, dict):
        return {k: dict_list_map_outplace(f, v) for k, v in x.items()}
    elif isinstance(x, list):
        return [dict_list_map_outplace(f, v) for v in x]
    else:
        return f(x)


def merge(x1: dict, x2: dict):
    if isinstance(x1, dict) and isinstance(x2, dict):
        for k, v2 in x2.items():
            if k not in x1:
                x1[k] = v2
            else:
                x1[k] = merge(x1[k], v2)
    elif isinstance(x1, list) and isinstance(x2, list):
        if len(x1) != len(x2):
            raise ValueError('Cannot merge two lists with different lengths')
        for i, v2 in enumerate(x2):
            x1[i] = merge(x1[i], v2)
    else:
        raise ValueError(f'Duplicate non-dict and non-list values encountered: `{x1}` and `{x2}`')
    return x1


def map_reduce(xs: Iterable, key_fn: Callable = lambda x: x,
               value_fn: Callable = lambda x: x, reduce_fn: Callable = lambda x: x) -> dict:
    res = defaultdict(list)
    for x in xs:
        res[key_fn(x)].append(value_fn(x))
    for k in res:
        res[k] = reduce_fn(res[k])
    return dict(res)
