# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Operators corresponding to Python builtin functions.

List of built-in functions: https://docs.python.org/3/library/functions.html
"""

import inspect

from nvidia.dali._autograph.utils import hooks


UNSPECIFIED = object()


def overload_of(f):
  if f in SUPPORTED_BUILTINS:
    return BUILTIN_FUNCTIONS_MAP[f.__name__]
  return f


def _find_originating_frame(caller_fn_scope, innermost=True):
  """Locates the frame in which `caller_fn_scope` was defined."""
  ctx_frame = inspect.currentframe()
  result = None
  while ctx_frame is not None:
    # Note it should not be normally possible to get false positives this way
    # because the function scope object is not accessible to user code (barring
    # call stack introspection).
    if ctx_frame.f_locals.get(caller_fn_scope.name, None) is caller_fn_scope:
      result = ctx_frame
      if innermost:
        break
    ctx_frame = ctx_frame.f_back

  assert result is not None, (
      'the conversion process should ensure the caller_fn_scope is always'
      ' found somewhere on the call stack')

  return result


def locals_in_original_context(caller_fn_scope):
  """Executes the locals function in the context of a specified function."""
  return _find_originating_frame(caller_fn_scope, innermost=True).f_locals


def globals_in_original_context(caller_fn_scope):
  """Executes the locals function in the context of a specified function."""
  return _find_originating_frame(caller_fn_scope, innermost=True).f_globals


def eval_in_original_context(f, args, caller_fn_scope):
  """Executes the eval function in the context of a specified function."""
  # When control flow is rewritten using functions, eval should use the
  # variables found in the same block where it was called. That is equivalent
  # to the innermost function call.
  ctx_frame = _find_originating_frame(caller_fn_scope, innermost=True)

  args = (
      args[0],
      ctx_frame.f_globals if len(args) < 2 else args[1],
      ctx_frame.f_locals if len(args) < 3 else args[2],
  )
  return f(*args)


def super_in_original_context(f, args, caller_fn_scope):
  """Executes the super function in the context of a specified function.

  See https://docs.python.org/3/library/functions.html#super for the exact
  details

  Args:
    f: Callable, typically the super builtin
    args: List[Any], the original call arguments
    caller_fn_scope: Optional[function_wrappers.FunctionScope], the function
      scope of the converted function in which this call was originally made

  Returns:
    The result of calling `f` as if it was called in the frame indicated by
      `caller_fn_scope`.
  """

  # Only the no-arg call is desugared.
  if args:
    return f(*args)

  # Inner functions seem to include their closure in f_locals, so we need
  # to find the outermost frame.
  ctx_frame = _find_originating_frame(caller_fn_scope, innermost=False)

  # When super(..) is called without arguments, it looks for __class__ cell
  # variable and the first argument passed in the enclosing function according
  # to the spec https://www.python.org/dev/peps/pep-3135/ .
  #
  # We couldn't verify if `inspect.currentframe().f_code.co_varnames[0]` is
  # guaranteed to be the first argument from an official doc or PEP, however,
  # it's fairly stable and well established:
  # - An unofficial community doc mentions it.
  #   https://python-reference.readthedocs.io/en/latest/docs/code/varnames.html
  # - CPython has tests checking that order, which was merged in 2008, and
  #   unchanged since then.
  #   https://github.com/python/cpython/blame/2f224a077a83ac9de8a12bb7dcc516642b8176d8/Lib/lib2to3/tests/data/py2_test_grammar.py#L157
  #   https://github.com/python/cpython/blame/2f224a077a83ac9de8a12bb7dcc516642b8176d8/Lib/lib2to3/tests/data/py3_test_grammar.py#L192
  #
  # Note: the name can be more reliably obtained by inspecting the calling
  # function's argspec.
  #
  # Even though methods can be declared using *args (def method(*args)),
  # that pattern is disallowed by super() -- it raises super() no arguments.
  # Method definitions using **kwargs are not allowed at all.
  # In other words, we can always assume that self is on the first positional
  # argument (for correct code).
  #
  # TODO(mdan): Consider additional checks in case the input code is incorrect.
  # For example, the error might be cryptic compared to what super() regularly
  # raises.

  type_arg = ctx_frame.f_locals['__class__']
  self_arg_name = ctx_frame.f_code.co_varnames[0]
  self_arg = ctx_frame.f_locals[self_arg_name]
  return f(type_arg, self_arg)


def abs_(x):
  if hooks._DISPATCH.detect_overload_abs_(x):
    return hooks._DISPATCH.abs_(x)
  return _py_abs(x)


def _py_abs(x):
  return abs(x)


def float_(x=0):
  if hooks._DISPATCH.detect_overload_float_(x):
    return hooks._DISPATCH.float_(x)
  return _py_float(x)


def _py_float(x):
  return float(x)


def int_(x=0, base=UNSPECIFIED):
  if hooks._DISPATCH.detect_overload_int_(x):
    return hooks._DISPATCH.int_(x, base)
  return _py_int(x, base)


def _py_int(x, base):
  if base is UNSPECIFIED:
    return int(x)
  return int(x, base)


def len_(s):
  if hooks._DISPATCH.detect_overload_len_(s):
    return hooks._DISPATCH.len_(s)
  return _py_len(s)


def _py_len(s):
  return len(s)


def print_(*objects, **kwargs):
  """Overload of the print builtin."""
  # Note: Python 2.6 doesn't support explicit keywords after starargs.
  unknown_kwargs = tuple(
      set(kwargs.keys()) - set(('sep', 'end', 'file', 'flush')))
  if unknown_kwargs:
    raise ValueError('invalid keyword arguments: {}'.format(unknown_kwargs))
  if hooks._DISPATCH.detect_overload_print_(objects):
    return hooks._DISPATCH.print_(objects, kwargs)
  else:
    _py_print(*objects, **kwargs)


def _py_print(*objects, **kwargs):
  print(*objects, **kwargs)


def min_(*args, **kwargs):
  if hooks._DISPATCH.detect_overload_min_(args):
    return hooks._DISPATCH.min_(*args, **kwargs)
  return _py_min(*args, **kwargs)


def _py_min(*args, **kwargs):
  return min(*args, **kwargs)


def max_(*args, **kwargs):
  if hooks._DISPATCH.detect_overload_max_(args):
    return hooks._DISPATCH.max_(*args, **kwargs)
  return _py_max(*args, **kwargs)


def _py_max(*args, **kwargs):
  return max(*args, **kwargs)


def range_(start_or_stop, stop=UNSPECIFIED, step=UNSPECIFIED):
  if hooks._DISPATCH.detect_overload_range_(start_or_stop, stop, step):
    return hooks._DISPATCH.range_(start_or_stop, stop, step)
  return _py_range(start_or_stop, stop, step)


def _py_range(start_or_stop, stop, step):
  if step is not UNSPECIFIED:
    return range(start_or_stop, stop, step)
  if stop is not UNSPECIFIED:
    return range(start_or_stop, stop)
  return range(start_or_stop)


def enumerate_(s, start=0):
  if hooks._DISPATCH.detect_overload_enumerate_(s):
    return hooks._DISPATCH.enumerate_(s, start)
  return _py_enumerate(s, start)


def _py_enumerate(s, start=0):
  return enumerate(s, start)


def zip_(*iterables):
  if hooks._DISPATCH.detect_overload_zip_(iterables):
    return hooks._DISPATCH.zip_(*iterables)
  return _py_zip(*iterables)


def _py_zip(*iterables):
  return zip(*iterables)


def map_(fn, *iterables):
  if hooks._DISPATCH.detect_overload_map_(iterables):
    return hooks._DISPATCH.map_(fn, *iterables)
  return _py_map(fn, *iterables)


def _py_map(fn, *iterables):
  return map(fn, *iterables)


def next_(iterator, default=UNSPECIFIED):
  if hooks._DISPATCH.detect_overload_next_(iterator):
    return hooks._DISPATCH.next_(iterator, default)
  return next_py(iterator, default)


def next_py(iterator, default=UNSPECIFIED):
  if default is UNSPECIFIED:
    return next(iterator)
  return next(iterator, default)


def filter_(function, iterable):
  if hooks._DISPATCH.detect_overload_filter_(iterable):
    return hooks._DISPATCH.filter_(function, iterable)
  return _py_filter(function, iterable)


def _py_filter(function, iterable):
  return filter(function, iterable)


def any_(iterable):
  if hooks._DISPATCH.detect_overload_any_(iterable):
    return hooks._DISPATCH.any_(iterable)
  return _py_any(iterable)


def _py_any(iterable):
  return any(iterable)


def all_(iterable):
  if hooks._DISPATCH.detect_overload_all_(iterable):
    return hooks._DISPATCH.all_(iterable)
  return _py_all(iterable)


def _py_all(iterable):
  return all(iterable)


def sorted_(iterable, key=UNSPECIFIED, reverse=UNSPECIFIED):
  if hooks._DISPATCH.detect_overload_sorted_(iterable):
    return hooks._DISPATCH.sorted_(iterable, key, reverse)
  return _py_sorted(iterable, key, reverse)


def _py_sorted(iterable, key, reverse):
  if key is not UNSPECIFIED and reverse is UNSPECIFIED:
    return sorted(iterable, key=key)
  if key is UNSPECIFIED and reverse is not UNSPECIFIED:
    return sorted(iterable, reverse=reverse)
  if key is not UNSPECIFIED and reverse is not UNSPECIFIED:
    return sorted(iterable, key=key, reverse=reverse)
  return sorted(iterable)


SUPPORTED_BUILTINS = (abs, float, int, len, print, range, enumerate, zip, map,
                      filter, any, all, sorted)

BUILTIN_FUNCTIONS_MAP = {
    'abs': abs_,
    'any': any_,
    'all': all_,
    'enumerate': enumerate_,
    'filter': filter_,
    'float': float_,
    'int': int_,
    'len': len_,
    'map': map_,
    'next': next_,
    'print': print_,
    'range': range_,
    'sorted': sorted_,
    'zip': zip_,
}
