def initial_positions(walls):
    """Calculate initial positions.

    Given the list of walls, returns the free positions that are closest to the
    bottom left and top right corner. The algorithm starts searching from
    (1, height-2) and (width-2, 1) respectively and uses the Manhattan distance
    for judging what is closest. On equal distances, a smaller distance in the
    x value is preferred.
    """
    width = max(walls)[0] + 1 # [STATE] width = 8 [/STATE]
    height = max(walls)[1] + 1 # [STATE] height = 4 [/STATE]

    left_start = (1, height - 2) # [STATE] left_start = (1, 2) [/STATE]
    left = [] # [STATE] left = [] [/STATE]
    right_start = (width - 2, 1) # [STATE] right_start = (6, 1) [/STATE]
    right = [] # [STATE] right = [] [/STATE]

    dist = 0 # [STATE] dist = 0 [/STATE]
    while len(left) < 2:
        # iterate through all possible x distances (inclusive)
        for x_dist in range(dist + 1): #  [STATE] x_dist = 0 [/STATE]
            y_dist = dist - x_dist #  [STATE] y_dist = 0 [/STATE] [STATE] y_dist = 1 [/STATE]
            pos = (left_start[0] + x_dist, left_start[1] - y_dist) #  [STATE] pos = (1, 2) [/STATE] [STATE] pos = (1, 1) [/STATE]
            # if both coordinates are out of bounds, we stop
            if not (0 <= pos[0] < width) and not (0 <= pos[1] < height):
                raise ValueError("Not enough free initial positions.")
            # if one coordinate is out of bounds, we just continue
            if not (0 <= pos[0] < width) or not (0 <= pos[1] < height):
                continue
            # check if the new value is free
            if pos not in walls:
                left.append(pos) #  [STATE] left = [(1, 2)] [/STATE] [STATE] left = [(1, 2), (1, 1)] [/STATE]

            if len(left) == 2:
                break

        dist += 1 #  [STATE] dist = 1 [/STATE] [STATE] dist = 2 [/STATE]

    dist = 0 # [STATE] dist = 0 [/STATE]
    while len(right) < 2:
        # iterate through all possible x distances (inclusive)
        for x_dist in range(dist + 1):
            y_dist = dist - x_dist #  [STATE] y_dist = 0 [/STATE] [STATE] y_dist = 1 [/STATE]
            pos = (right_start[0] - x_dist, right_start[1] + y_dist) #  [STATE] pos = (6, 1) [/STATE] [STATE] pos = (6, 2) [/STATE]
            # if both coordinates are out of bounds, we stop
            if not (0 <= pos[0] < width) and not (0 <= pos[1] < height):
                raise ValueError("Not enough free initial positions.")
            # if one coordinate is out of bounds, we just continue
            if not (0 <= pos[0] < width) or not (0 <= pos[1] < height):
                continue
            # check if the new value is free
            if pos not in walls:
                right.append(pos) #  [STATE] right = [(6, 1)] [/STATE] [STATE] right = [(6, 1), (6, 2)] [/STATE]

            if len(right) == 2:
                break

        dist += 1 #  [STATE] dist = 1 [/STATE] [STATE] dist = 2 [/STATE]

    # lower indices start further away
    left.reverse() # [STATE] left = [(1, 1), (1, 2)] [/STATE]
    right.reverse() # [STATE] right = [(6, 2), (6, 1)] [/STATE]
    return [left[0], right[0], left[1], right[1]]

initial_positions([(0, 0), (0, 1), (0, 2), (0, 3), (1, 0), (1, 3), (2, 0), (2, 1), (2, 3), (3, 0), (3, 1), (3, 3), (4, 0), (4, 1), (4, 3), (5, 0), (5, 3), (6, 0), (6, 3), (7, 0), (7, 1), (7, 2), (7, 3)])

1: def initial_positions(walls):
2:     """Calculate initial positions.
3:
4:     Given the list of walls, returns the free positions that are closest to the
5:     bottom left and top right corner. The algorithm starts searching from
6:     (1, height-2) and (width-2, 1) respectively and uses the Manhattan distance
7:     for judging what is closest. On equal distances, a smaller distance in the
8:     x value is preferred.
9:     """
10:     width = max(walls)[0] + 1
11:     height = max(walls)[1] + 1
12:
13:     left_start = (1, height - 2)
14:     left = []
15:     right_start = (width - 2, 1)
16:     right = []
17:
18:     dist = 0
19:     while len(left) < 2:
20:         # iterate through all possible x distances (inclusive)
21:         for x_dist in range(dist + 1):
22:             y_dist = dist - x_dist
23:             pos = (left_start[0] + x_dist, left_start[1] - y_dist)
24:             # if both coordinates are out of bounds, we stop
25:             if not (0 <= pos[0] < width) and not (0 <= pos[1] < height):
26:                 raise ValueError("Not enough free initial positions.")
27:             # if one coordinate is out of bounds, we just continue
28:             if not (0 <= pos[0] < width) or not (0 <= pos[1] < height):
29:                 continue
30:             # check if the new value is free
31:             if pos not in walls:
32:                 left.append(pos)
33:
34:             if len(left) == 2:
35:                 break
36:
37:         dist += 1
38:
39:     dist = 0
40:     while len(right) < 2:
41:         # iterate through all possible x distances (inclusive)
42:         for x_dist in range(dist + 1):
43:             y_dist = dist - x_dist
44:             pos = (right_start[0] - x_dist, right_start[1] + y_dist)
45:             # if both coordinates are out of bounds, we stop
46:             if not (0 <= pos[0] < width) and not (0 <= pos[1] < height):
47:                 raise ValueError("Not enough free initial positions.")
48:             # if one coordinate is out of bounds, we just continue
49:             if not (0 <= pos[0] < width) or not (0 <= pos[1] < height):
50:                 continue
51:             # check if the new value is free
52:             if pos not in walls:
53:                 right.append(pos)
54:
55:             if len(right) == 2:
56:                 break
57:
58:         dist += 1
59:
60:     # lower indices start further away
61:     left.reverse()
62:     right.reverse()
63:     return [left[0], right[0], left[1], right[1]]
64:
65: initial_positions([(0, 0), (0, 1), (0, 2), (0, 3), (1, 0), (1, 3), (2, 0), (2, 1), (2, 3), (3, 0), (3, 1), (3, 3), (4, 0), (4, 1), (4, 3), (5, 0), (5, 3), (6, 0), (6, 3), (7, 0), (7, 1), (7, 2), (7, 3)])

Question: What is the value of ' y_dist ' in line '22' after '1' th iteration when 'initial_positions([(0, 0), (0, 1), (0, 2), (0, 3), (1, 0), (1, 3), (2, 0), (2, 1), (2, 3), (3, 0), (3, 1), (3, 3), (4, 0), (4, 1), (4, 3), (5, 0), (5, 3), (6, 0), (6, 3), (7, 0), (7, 1), (7, 2), (7, 3)])' is executed?

Answer: 0


def extend(*args):
        args = list(args) # [STATE] args = [{}, {}] [/STATE]
        dest = args.pop(0) # [STATE] dest = {} [/STATE] # [STATE] args = [{}] [/STATE]
        for source in args: #  [STATE] source = {} [/STATE]
            if source:
                dest.update(source)
        return dest

extend(({}, {}))

1: def extend(*args):
2:         args = list(args)
3:         dest = args.pop(0)
4:         for source in args:
5:             if source:
6:                 dest.update(source)
7:         return dest
8:
9: extend(({}, {}))

Question: What is the value of ' source ' in line '4' after '1' th iteration when 'extend(({}, {}))' is executed?


def notification_event(events):
    """
    Property: NotificationConfig.NotificationEvents
    """

    valid_events = ["All", "InProgress", "Success", "TimedOut", "Cancelled", "Failed"] # [STATE] valid_events = ['All', 'InProgress', 'Success', 'TimedOut', 'Cancelled', 'Failed'] [/STATE]
    for event in events: #  [STATE] event = 'All' [/STATE] [STATE] event = 'InProgress' [/STATE] [STATE] event = 'Success' [/STATE] [STATE] event = 'TimedOut' [/STATE] [STATE] event = 'Cancelled' [/STATE] [STATE] event = 'Failed' [/STATE]
        if event not in valid_events:
            raise ValueError(
                'NotificationEvents must be at least one of: "%s"'
                % (", ".join(valid_events))
            )
    return events

notification_event(['All', 'InProgress', 'Success', 'TimedOut', 'Cancelled', 'Failed'])

1: def notification_event(events):
2:     """
3:     Property: NotificationConfig.NotificationEvents
4:     """
5:
6:     valid_events = ["All", "InProgress", "Success", "TimedOut", "Cancelled", "Failed"]
7:     for event in events:
8:         if event not in valid_events:
9:             raise ValueError(
10:                 'NotificationEvents must be at least one of: "%s"'
11:                 % (", ".join(valid_events))
12:             )
13:     return events
14:
15: notification_event(['All', 'InProgress', 'Success', 'TimedOut', 'Cancelled', 'Failed'])

Question: What is the value of ' event ' in line '7' after '5' th iteration when 'notification_event(['All', 'InProgress', 'Success', 'TimedOut', 'Cancelled', 'Failed'])' is executed?

Answer: 'Cancelled'


def _LiteralEval(value):
  """Parse value as a Python literal, or container of containers and literals.

  First the AST of the value is updated so that bare-words are turned into
  strings. Then the resulting AST is evaluated as a literal or container of
  only containers and literals.

  This allows for the YAML-like syntax {a: b} to represent the dict {'a': 'b'}

  Args:
    value: A string to be parsed as a literal or container of containers and
      literals.
  Returns:
    The Python value representing the value arg.
  Raises:
    ValueError: If the value is not an expression with only containers and
      literals.
    SyntaxError: If the value string has a syntax error.
  """
  root = ast.parse(value, mode='eval') # [STATE] root = {body=<ast.List object at 0x7f29d94a6b80>} [/STATE]
  if isinstance(root.body, ast.BinOp):
    raise ValueError(value)

  for node in ast.walk(root): #  [STATE] node = {body=<ast.List object at 0x7f29d94a6b80>} [/STATE] [STATE] node = {elts=[<ast.Name object at 0x7f29d94a6d00>, <ast.Constant object at 0x7f29d94a6610>, <ast.Constant object at 0x7f29d94a6d30>], ctx=<ast.Load object at 0x7f29db3ac520>, lineno=1, col_offset=0, end_lineno=1, end_col_offset=13} [/STATE] [STATE] node = {id='one', ctx=<ast.Load object at 0x7f29db3ac520>, lineno=1, col_offset=1, end_lineno=1, end_col_offset=4} [/STATE] [STATE] node = {value=2, kind=None, lineno=1, col_offset=6, end_lineno=1, end_col_offset=7} [/STATE] [STATE] node = {value='3', kind=None, lineno=1, col_offset=9, end_lineno=1, end_col_offset=12} [/STATE] [STATE] node = {} [/STATE]
    for field, child in ast.iter_fields(node): #  [STATE] field = 'body' [/STATE] [STATE] child = {elts=[<ast.Name object at 0x7f29d94a6d00>, <ast.Constant object at 0x7f29d94a6610>, <ast.Constant object at 0x7f29d94a6d30>], ctx=<ast.Load object at 0x7f29db3ac520>, lineno=1, col_offset=0, end_lineno=1, end_col_offset=13} [/STATE] [STATE] field = 'elts' [/STATE] [STATE] child = [<ast.Name object at 0x7f29d94a6d00>, <ast.Constant object at 0x7f29d94a6610>, <ast.Constant object at 0x7f29d94a6d30>] [/STATE] [STATE] field = 'ctx' [/STATE] [STATE] child = {} [/STATE] [STATE] field = 'id' [/STATE] [STATE] child = 'one' [/STATE] [STATE] field = 'value' [/STATE] [STATE] child = 2 [/STATE] [STATE] field = 'kind' [/STATE] [STATE] child = None [/STATE] [STATE] child = '3' [/STATE]
      if isinstance(child, list):
        for index, subchild in enumerate(child): #  [STATE] index = 0 [/STATE] [STATE] subchild = {id='one', ctx=<ast.Load object at 0x7f29db3ac520>, lineno=1, col_offset=1, end_lineno=1, end_col_offset=4} [/STATE] [STATE] index = 1 [/STATE] [STATE] subchild = {value=2, kind=None, lineno=1, col_offset=6, end_lineno=1, end_col_offset=7} [/STATE] [STATE] index = 2 [/STATE] [STATE] subchild = {value='3', kind=None, lineno=1, col_offset=9, end_lineno=1, end_col_offset=12} [/STATE]
          if isinstance(subchild, ast.Name):
            child[index] = _Replacement(subchild) # [STATE] node = {elts=[<ast.Constant object at 0x7f29d94a6e80>, <ast.Constant object at 0x7f29d94a6610>, <ast.Constant object at 0x7f29d94a6d30>], ctx=<ast.Load object at 0x7f29db3ac520>, lineno=1, col_offset=0, end_lineno=1, end_col_offset=13} [/STATE] # [STATE] child = [<ast.Constant object at 0x7f29d94a6e80>, <ast.Constant object at 0x7f29d94a6610>, <ast.Constant object at 0x7f29d94a6d30>] [/STATE]

      elif isinstance(child, ast.Name):
        replacement = _Replacement(child)
        node.__setattr__(field, replacement)

  # ast.literal_eval supports the following types:
  # strings, bytes, numbers, tuples, lists, dicts, sets, booleans, and None
  # (bytes and set literals only starting with Python 3.2)
  return ast.literal_eval(root)

_LiteralEval('[one, 2, "3"]')

1: def _LiteralEval(value):
2:   """Parse value as a Python literal, or container of containers and literals.
3:
4:   First the AST of the value is updated so that bare-words are turned into
5:   strings. Then the resulting AST is evaluated as a literal or container of
6:   only containers and literals.
7:
8:   This allows for the YAML-like syntax {a: b} to represent the dict {'a': 'b'}
9:
10:   Args:
11:     value: A string to be parsed as a literal or container of containers and
12:       literals.
13:   Returns:
14:     The Python value representing the value arg.
15:   Raises:
16:     ValueError: If the value is not an expression with only containers and
17:       literals.
18:     SyntaxError: If the value string has a syntax error.
19:   """
20:   root = ast.parse(value, mode='eval')
21:   if isinstance(root.body, ast.BinOp):
22:     raise ValueError(value)
23:
24:   for node in ast.walk(root):
25:     for field, child in ast.iter_fields(node):
26:       if isinstance(child, list):
27:         for index, subchild in enumerate(child):
28:           if isinstance(subchild, ast.Name):
29:             child[index] = _Replacement(subchild)
30:
31:       elif isinstance(child, ast.Name):
32:         replacement = _Replacement(child)
33:         node.__setattr__(field, replacement)
34:
35:   # ast.literal_eval supports the following types:
36:   # strings, bytes, numbers, tuples, lists, dicts, sets, booleans, and None
37:   # (bytes and set literals only starting with Python 3.2)
38:   return ast.literal_eval(root)
39:
40: _LiteralEval('[one, 2, "3"]')

Question: What is the value of ' child ' in line '29' after '2' th iteration when '_LiteralEval('[one, 2, "3"]')' is executed?

Answer: [<ast.Constant object at 0x7f29d94a6e80>, <ast.Constant object at 0x7f29d94a6610>, <ast.Constant object at 0x7f29d94a6d30>]


def prepare_docstring_help(N):
    """Replace docstrings to include the parameters (schema)"""
    # at this point, the params have not yet been populated

    args = [] # [STATE] args = [] [/STATE]
    if hasattr(N, '__annotations__'):
        for attr_name, cls in N.__annotations__.items(): #  [STATE] attr_name = 'bar' [/STATE] [STATE] cls = <class 'int'> [/STATE]

            filtered = filter_params(N) # [STATE] filtered = ['            bar: int = 0\n'] [/STATE]
            parsed = parse_source_for_params(filtered) # [STATE] parsed = OrderedDict([('bar: int', '0')]) [/STATE]
            attr = attr_map(parsed).get(attr_name) # [STATE] attr = {'type': 'int', 'default': '0', 'description': ''} [/STATE]
            if attr is None:
                continue

            args.append(argument_help(attr_name, attr)) # [STATE] args = ['    --bar (int):  (Default is 0)'] [/STATE]

    return '\n'.join(args)

prepare_docstring_help({})

1: def prepare_docstring_help(N):
2:     """Replace docstrings to include the parameters (schema)"""
3:     # at this point, the params have not yet been populated
4:
5:     args = []
6:     if hasattr(N, '__annotations__'):
7:         for attr_name, cls in N.__annotations__.items():
8:
9:             filtered = filter_params(N)
10:             parsed = parse_source_for_params(filtered)
11:             attr = attr_map(parsed).get(attr_name)
12:             if attr is None:
13:                 continue
14:
15:             args.append(argument_help(attr_name, attr))
16:
17:     return '\n'.join(args)
18:
19: prepare_docstring_help({})

Question: What is the value of ' filtered ' in line '9' after '1' th iteration when 'prepare_docstring_help({})' is executed?

Answer: ['            bar: int

filtered = ['            bar: int = 0\n']


def filter_params(N):
    """Filter source lines of the class
    Returns:
        fields as source lines
    """
    filtered_source = [] # [STATE] filtered_source = [] [/STATE]
    for line in inspect.getsourcelines(N.__class__)[0][1:]: #  [STATE] line = '            bar: int = 0\n' [/STATE]
        # When parsing, post_init would bleed into the attributes without this hack
        if line.strip().startswith('def '):
            break
        filtered_source.append(line) # [STATE] filtered_source = ['            bar: int = 0\n'] [/STATE]
    return filtered_source

filter_params({})

1: def filter_params(N):
2:     """Filter source lines of the class
3:     Returns:
4:         fields as source lines
5:     """
6:     filtered_source = []
7:     for line in inspect.getsourcelines(N.__class__)[0][1:]:
8:         # When parsing, post_init would bleed into the attributes without this hack
9:         if line.strip().startswith('def '):
10:             break
11:         filtered_source.append(line)
12:     return filtered_source
13:
14: filter_params({})

Question: What is the value of ' filtered_source ' in line '11' after '1' th iteration when 'filter_params({})' is executed?

Answer: ['            bar: int

filtered_source = ['            bar: int = 0\n']


def filter_fields(d: dict, nt):
    """Excludes fields not found in the schema/namedtuple"""
    res = {} # [STATE] res = {} [/STATE]
    for k, v in d.items(): #  [STATE] k = 'bar' [/STATE] [STATE] v = '42' [/STATE]
        if k in nt._fields:
            res.update({k: v}) # [STATE] res = {'bar': '42'} [/STATE]

    return res

filter_fields({'bar': '42'}, {})

1: def filter_fields(d: dict, nt):
2:     """Excludes fields not found in the schema/namedtuple"""
3:     res = {}
4:     for k, v in d.items():
5:         if k in nt._fields:
6:             res.update({k: v})
7:
8:     return res
9:
10: filter_fields({'bar': '42'}, {})

Question: What is the value of ' res ' in line '6' after '1' th iteration when 'filter_fields({'bar': '42'}, {})' is executed?

Answer: {'bar': '42'}


def type_correct_with(cdict, cfg_tuple):
    """Use type hints of the cfg tuple to cast parameters i.e. attributes into their intended types"""
    # TODO: This would be cleaner, if the config would use Schema or derivative in the
    # first place and use its validation process
    res = {} # [STATE] res = {} [/STATE]
    for k, v in cdict.items(): #  [STATE] k = 'bar' [/STATE] [STATE] v = '42' [/STATE]
        typename = getattr(cfg_tuple, k) # [STATE] typename = 0 [/STATE]
        res.update({k: type(typename)(v)}) # [STATE] res = {'bar': 42} [/STATE]
    return res

type_correct_with({'bar': '42'}, {})

1: def type_correct_with(cdict, cfg_tuple):
2:     """Use type hints of the cfg tuple to cast parameters i.e. attributes into their intended types"""
3:     # TODO: This would be cleaner, if the config would use Schema or derivative in the
4:     # first place and use its validation process
5:     res = {}
6:     for k, v in cdict.items():
7:         typename = getattr(cfg_tuple, k)
8:         res.update({k: type(typename)(v)})
9:     return res
10:
11: type_correct_with({'bar': '42'}, {})

Question: What is the value of ' typename ' in line '7' after '1' th iteration when 'type_correct_with({'bar': '42'}, {})' is executed?

Answer: 0


def process_fenced_block(lines, start_line_num):
    for line_num in range(start_line_num, len(lines)): #  [STATE] line_num = 4 [/STATE] [STATE] line_num = 5 [/STATE] [STATE] line_num = 6 [/STATE] [STATE] line_num = 7 [/STATE] [STATE] line_num = 8 [/STATE] [STATE] line_num = 9 [/STATE]
        line = lines[line_num] #  [STATE] line = '--- /dev/null\n' [/STATE] [STATE] line = '+++ file.txt\n' [/STATE] [STATE] line = '@@ ... @@\n' [/STATE] [STATE] line = '-Original\n' [/STATE] [STATE] line = '+Modified\n' [/STATE] [STATE] line = '```\n' [/STATE]
        if line.startswith("```"):
            break

    block = lines[start_line_num:line_num] # [STATE] block = ['--- /dev/null\n', '+++ file.txt\n', '@@ ... @@\n', '-Original\n', '+Modified\n'] [/STATE]
    block.append("@@ @@") # [STATE] block = ['--- /dev/null\n', '+++ file.txt\n', '@@ ... @@\n', '-Original\n', '+Modified\n', '@@ @@'] [/STATE]

    if block[0].startswith("--- ") and block[1].startswith("+++ "):
        # Extract the file path, considering that it might contain spaces
        fname = block[1][4:].strip() # [STATE] fname = 'file.txt' [/STATE]
        block = block[2:] # [STATE] block = ['@@ ... @@\n', '-Original\n', '+Modified\n', '@@ @@'] [/STATE]
    else:
        fname = None

    edits = [] # [STATE] edits = [] [/STATE]

    keeper = False # [STATE] keeper = False [/STATE]
    hunk = [] # [STATE] hunk = [] [/STATE]
    op = " " # [STATE] op = ' ' [/STATE]
    for line in block: #  [STATE] line = '@@ ... @@\n' [/STATE] [STATE] line = '-Original\n' [/STATE] [STATE] line = '+Modified\n' [/STATE] [STATE] line = '@@ @@' [/STATE]
        hunk.append(line) #  [STATE] hunk = ['@@ ... @@\n'] [/STATE] [STATE] hunk = ['-Original\n'] [/STATE] [STATE] hunk = ['-Original\n', '+Modified\n'] [/STATE] [STATE] hunk = ['-Original\n', '+Modified\n', '@@ @@'] [/STATE]
        if len(line) < 2:
            continue

        if line.startswith("+++ ") and hunk[-2].startswith("--- "):
            if hunk[-3] == "\n":
                hunk = hunk[:-3]
            else:
                hunk = hunk[:-2]

            edits.append((fname, hunk))
            hunk = []
            keeper = False

            fname = line[4:].strip()
            continue

        op = line[0] #  [STATE] op = '@' [/STATE] [STATE] op = '-' [/STATE] [STATE] op = '+' [/STATE]
        if op in "-+":
            keeper = True #  [STATE] keeper = True [/STATE]
            continue
        if op != "@":
            continue
        if not keeper:
            hunk = [] # [STATE] hunk = [] [/STATE]
            continue

        hunk = hunk[:-1] # [STATE] hunk = ['-Original\n', '+Modified\n'] [/STATE]
        edits.append((fname, hunk)) # [STATE] edits = [('file.txt', ['-Original\n', '+Modified\n'])] [/STATE]
        hunk = [] # [STATE] hunk = [] [/STATE]
        keeper = False # [STATE] keeper = False [/STATE]

    return line_num + 1, edits

process_fenced_block(['\n', 'Some text...\n', '\n', '```diff\n', '--- /dev/null\n', '+++ file.txt\n', '@@ ... @@\n', '-Original\n', '+Modified\n', '```\n'], 4)

1: def process_fenced_block(lines, start_line_num):
2:     for line_num in range(start_line_num, len(lines)):
3:         line = lines[line_num]
4:         if line.startswith("```"):
5:             break
6:
7:     block = lines[start_line_num:line_num]
8:     block.append("@@ @@")
9:
10:     if block[0].startswith("--- ") and block[1].startswith("+++ "):
11:         # Extract the file path, considering that it might contain spaces
12:         fname = block[1][4:].strip()
13:         block = block[2:]
14:     else:
15:         fname = None
16:
17:     edits = []
18:
19:     keeper = False
20:     hunk = []
21:     op = " "
22:     for line in block:
23:         hunk.append(line)
24:         if len(line) < 2:
25:             continue
26:
27:         if line.startswith("+++ ") and hunk[-2].startswith("--- "):
28:             if hunk[-3] == "\n":
29:                 hunk = hunk[:-3]
30:             else:
31:                 hunk = hunk[:-2]
32:
33:             edits.append((fname, hunk))
34:             hunk = []
35:             keeper = False
36:
37:             fname = line[4:].strip()
38:             continue
39:
40:         op = line[0]
41:         if op in "-+":
42:             keeper = True
43:             continue
44:         if op != "@":
45:             continue
46:         if not keeper:
47:             hunk = []
48:             continue
49:
50:         hunk = hunk[:-1]
51:         edits.append((fname, hunk))
52:         hunk = []
53:         keeper = False
54:
55:     return line_num + 1, edits
56:
57: process_fenced_block(['\n', 'Some text...\n', '\n', '```diff\n', '--- /dev/null\n', '+++ file.txt\n', '@@ ... @@\n', '-Original\n', '+Modified\n', '```\n'], 4)

Question: What is the value of ' line ' in line '3' after '6' th iteration when 'process_fenced_block(['\n', 'Some text...\n', '\n', '```diff\n', '--- /dev/null\n', '+++ file.txt\n', '@@ ... @@\n', '-Original\n', '+Modified\n', '```\n'], 4)' is executed?

Answer: '```\n'


Question: What is the value of ' line ' in line '4' after '4' th iteration when 'assert_newlines(['0\n', '1\n', '2\n', '3\n', '4\n', '5\n', '6\n', '7\n', '8\n', '9\n', '10\n', '11\n', '12\n', '13\n', '14\n', '15\n', '16\n', '17\n', '18\n', '19\n', '20\n', '21\n', '22\n', '23\n', '24\n', '25\n', '26\n', '27\n', '28\n', '29\n', '30\n', '31\n', '32\n', '33\n', '34\n', '35\n', '36\n', '37\n', '38\n', '39\n', '40\n', '41\n', '42\n', '43\n', '44\n', '45\n', '46\n', '47\n', '48\n', '49\n', '50\n', '51\n', '52\n', '53\n', '54\n', '55\n', '56\n', '57\n', '58\n', '59\n', '60\n', '61\n', '62\n', '63\n', '64\n', '65\n', '66\n', '67\n', '68\n', '69\n', '70\n', '71\n', '72\n', '73\n', '74\n', '75\n', '76\n', '77\n', '78\n', '79\n', '80\n', '81\n', '82\n', '83\n', '84\n', '85\n', '86\n', '87\n', '88\n', '89\n', '90\n', '91\n', '92\n', '93\n', '94\n', '95\n', '96\n', '97\n', '98\n', '99'])' is executed?

Answer: '3\n'


def flatten(d, parent_key="", sep="/") -> Dict[str, Any]:
    """Flatten a dictionary.

    Source: https://stackoverflow.com/questions/6027558/flatten-nested-dictionaries-compressing-keys

    Parameters
    ----------
    d : Dict
        The dictionary to flatten.
    parent_key : str, optional
        The parent key, by default ""
    sep : str, optional
        The separator to use, by default "/"

    Returns
    -------
    Dict[str, Any]
        The flattened dictionary.
    """
    items: List[Tuple[str, List[str]]] = [] # [STATE] items = [] [/STATE]
    for k, v in d.items(): #  [STATE] k = 'top' [/STATE] [STATE] v = ['CoinGecko', 'CoinMarketCap'] [/STATE] [STATE] k = 'trending' [/STATE] [STATE] v = ['CoinGecko'] [/STATE] [STATE] k = 'gainers' [/STATE] [STATE] k = 'losers' [/STATE] [STATE] k = 'search' [/STATE] [STATE] v = ['CoinPaprika'] [/STATE] [STATE] k = 'nft_mktp_chains' [/STATE] [STATE] v = ['DappRadar'] [/STATE] [STATE] k = 'nft_mktp' [/STATE] [STATE] k = 'dapps' [/STATE] [STATE] k = 'dapp_categories' [/STATE] [STATE] k = 'dapp_chains' [/STATE] [STATE] k = 'dapp_metrics' [/STATE] [STATE] k = 'defi_chains' [/STATE] [STATE] k = 'tokens' [/STATE] [STATE] k = 'fees' [/STATE] [STATE] v = ['Cryptostats'] [/STATE]
        new_key = parent_key + sep + k if parent_key else k #  [STATE] new_key = 'crypto/disc/top' [/STATE] [STATE] new_key = 'crypto/disc/trending' [/STATE] [STATE] new_key = 'crypto/disc/gainers' [/STATE] [STATE] new_key = 'crypto/disc/losers' [/STATE] [STATE] new_key = 'crypto/disc/search' [/STATE] [STATE] new_key = 'crypto/disc/nft_mktp_chains' [/STATE] [STATE] new_key = 'crypto/disc/nft_mktp' [/STATE] [STATE] new_key = 'crypto/disc/dapps' [/STATE] [STATE] new_key = 'crypto/disc/dapp_categories' [/STATE] [STATE] new_key = 'crypto/disc/dapp_chains' [/STATE] [STATE] new_key = 'crypto/disc/dapp_metrics' [/STATE] [STATE] new_key = 'crypto/disc/defi_chains' [/STATE] [STATE] new_key = 'crypto/disc/tokens' [/STATE] [STATE] new_key = 'crypto/disc/fees' [/STATE]
        if isinstance(v, MutableMapping):
            items.extend(flatten(v, new_key, sep=sep).items())
        else:
            items.append((new_key, v)) #  [STATE] items = [('crypto/disc/top', ['CoinGecko', 'CoinMarketCap'])] [/STATE] [STATE] items = [('crypto/disc/top', ['CoinGecko', 'CoinMarketCap']), ('crypto/disc/trending', ['CoinGecko'])] [/STATE] [STATE] items = [('crypto/disc/top', ['CoinGecko', 'CoinMarketCap']), ('crypto/disc/trending', ['CoinGecko']), ('crypto/disc/gainers', ['CoinGecko'])] [/STATE] [STATE] items = [('crypto/disc/top', ['CoinGecko', 'CoinMarketCap']), ('crypto/disc/trending', ['CoinGecko']), ('crypto/disc/gainers', ['CoinGecko']), ('crypto/disc/losers', ['CoinGecko'])] [/STATE] [STATE] items = [('crypto/disc/top', ['CoinGecko', 'CoinMarketCap']), ('crypto/disc/trending', ['CoinGecko']), ('crypto/disc/gainers', ['CoinGecko']), ('crypto/disc/losers', ['CoinGecko']), ('crypto/disc/search', ['CoinPaprika'])] [/STATE] [STATE] items = [('crypto/disc/top', ['CoinGecko', 'CoinMarketCap']), ('crypto/disc/trending', ['CoinGecko']), ('crypto/disc/gainers', ['CoinGecko']), ('crypto/disc/losers', ['CoinGecko']), ('crypto/disc/search', ['CoinPaprika']), ('crypto/disc/nft_mktp_chains', ['DappRadar'])] [/STATE] [STATE] items = [('crypto/disc/top', ['CoinGecko', 'CoinMarketCap']), ('crypto/disc/trending', ['CoinGecko']), ('crypto/disc/gainers', ['CoinGecko']), ('crypto/disc/losers', ['CoinGecko']), ('crypto/disc/search', ['CoinPaprika']), ('crypto/disc/nft_mktp_chains', ['DappRadar']), ('crypto/disc/nft_mktp', ['DappRadar'])] [/STATE] [STATE] items = [('crypto/disc/top', ['CoinGecko', 'CoinMarketCap']), ('crypto/disc/trending', ['CoinGecko']), ('crypto/disc/gainers', ['CoinGecko']), ('crypto/disc/losers', ['CoinGecko']), ('crypto/disc/search', ['CoinPaprika']), ('crypto/disc/nft_mktp_chains', ['DappRadar']), ('crypto/disc/nft_mktp', ['DappRadar']), ('crypto/disc/dapps', ['DappRadar'])] [/STATE] [STATE] items = [('crypto/disc/top', ['CoinGecko', 'CoinMarketCap']), ('crypto/disc/trending', ['CoinGecko']), ('crypto/disc/gainers', ['CoinGecko']), ('crypto/disc/losers', ['CoinGecko']), ('crypto/disc/search', ['CoinPaprika']), ('crypto/disc/nft_mktp_chains', ['DappRadar']), ('crypto/disc/nft_mktp', ['DappRadar']), ('crypto/disc/dapps', ['DappRadar']), ('crypto/disc/dapp_categories', ['DappRadar'])] [/STATE] [STATE] items = [('crypto/disc/top', ['CoinGecko', 'CoinMarketCap']), ('crypto/disc/trending', ['CoinGecko']), ('crypto/disc/gainers', ['CoinGecko']), ('crypto/disc/losers', ['CoinGecko']), ('crypto/disc/search', ['CoinPaprika']), ('crypto/disc/nft_mktp_chains', ['DappRadar']), ('crypto/disc/nft_mktp', ['DappRadar']), ('crypto/disc/dapps', ['DappRadar']), ('crypto/disc/dapp_categories', ['DappRadar']), ('crypto/disc/dapp_chains', ['DappRadar'])] [/STATE] [STATE] items = [('crypto/disc/top', ['CoinGecko', 'CoinMarketCap']), ('crypto/disc/trending', ['CoinGecko']), ('crypto/disc/gainers', ['CoinGecko']), ('crypto/disc/losers', ['CoinGecko']), ('crypto/disc/search', ['CoinPaprika']), ('crypto/disc/nft_mktp_chains', ['DappRadar']), ('crypto/disc/nft_mktp', ['DappRadar']), ('crypto/disc/dapps', ['DappRadar']), ('crypto/disc/dapp_categories', ['DappRadar']), ('crypto/disc/dapp_chains', ['DappRadar']), ('crypto/disc/dapp_metrics', ['DappRadar'])] [/STATE] [STATE] items = [('crypto/disc/top', ['CoinGecko', 'CoinMarketCap']), ('crypto/disc/trending', ['CoinGecko']), ('crypto/disc/gainers', ['CoinGecko']), ('crypto/disc/losers', ['CoinGecko']), ('crypto/disc/search', ['CoinPaprika']), ('crypto/disc/nft_mktp_chains', ['DappRadar']), ('crypto/disc/nft_mktp', ['DappRadar']), ('crypto/disc/dapps', ['DappRadar']), ('crypto/disc/dapp_categories', ['DappRadar']), ('crypto/disc/dapp_chains', ['DappRadar']), ('crypto/disc/dapp_metrics', ['DappRadar']), ('crypto/disc/defi_chains', ['DappRadar'])] [/STATE] [STATE] items = [('crypto/disc/top', ['CoinGecko', 'CoinMarketCap']), ('crypto/disc/trending', ['CoinGecko']), ('crypto/disc/gainers', ['CoinGecko']), ('crypto/disc/losers', ['CoinGecko']), ('crypto/disc/search', ['CoinPaprika']), ('crypto/disc/nft_mktp_chains', ['DappRadar']), ('crypto/disc/nft_mktp', ['DappRadar']), ('crypto/disc/dapps', ['DappRadar']), ('crypto/disc/dapp_categories', ['DappRadar']), ('crypto/disc/dapp_chains', ['DappRadar']), ('crypto/disc/dapp_metrics', ['DappRadar']), ('crypto/disc/defi_chains', ['DappRadar']), ('crypto/disc/tokens', ['DappRadar'])] [/STATE] [STATE] items = [('crypto/disc/top', ['CoinGecko', 'CoinMarketCap']), ('crypto/disc/trending', ['CoinGecko']), ('crypto/disc/gainers', ['CoinGecko']), ('crypto/disc/losers', ['CoinGecko']), ('crypto/disc/search', ['CoinPaprika']), ('crypto/disc/nft_mktp_chains', ['DappRadar']), ('crypto/disc/nft_mktp', ['DappRadar']), ('crypto/disc/dapps', ['DappRadar']), ('crypto/disc/dapp_categories', ['DappRadar']), ('crypto/disc/dapp_chains', ['DappRadar']), ('crypto/disc/dapp_metrics', ['DappRadar']), ('crypto/disc/defi_chains', ['DappRadar']), ('crypto/disc/tokens', ['DappRadar']), ('crypto/disc/fees', ['Cryptostats'])] [/STATE]
    return dict(items)

flatten({'top': ['CoinGecko', 'CoinMarketCap'], 'trending': ['CoinGecko'], 'gainers': ['CoinGecko'], 'losers': ['CoinGecko'], 'search': ['CoinPaprika'], 'nft_mktp_chains': ['DappRadar'], 'nft_mktp': ['DappRadar'], 'dapps': ['DappRadar'], 'dapp_categories': ['DappRadar'], 'dapp_chains': ['DappRadar'], 'dapp_metrics': ['DappRadar'], 'defi_chains': ['DappRadar'], 'tokens': ['DappRadar'], 'fees': ['Cryptostats']}, 'crypto/disc', '/')

1: def flatten(d, parent_key="", sep="/") -> Dict[str, Any]:
2:     """Flatten a dictionary.
3:
4:     Source: https://stackoverflow.com/questions/6027558/flatten-nested-dictionaries-compressing-keys
5:
6:     Parameters
7:     ----------
8:     d : Dict
9:         The dictionary to flatten.
10:     parent_key : str, optional
11:         The parent key, by default ""
12:     sep : str, optional
13:         The separator to use, by default "/"
14:
15:     Returns
16:     -------
17:     Dict[str, Any]
18:         The flattened dictionary.
19:     """
20:     items: List[Tuple[str, List[str]]] = []
21:     for k, v in d.items():
22:         new_key = parent_key + sep + k if parent_key else k
23:         if isinstance(v, MutableMapping):
24:             items.extend(flatten(v, new_key, sep=sep).items())
25:         else:
26:             items.append((new_key, v))
27:     return dict(items)
28:
29: flatten({'top': ['CoinGecko', 'CoinMarketCap'], 'trending': ['CoinGecko'], 'gainers': ['CoinGecko'], 'losers': ['CoinGecko'], 'search': ['CoinPaprika'], 'nft_mktp_chains': ['DappRadar'], 'nft_mktp': ['DappRadar'], 'dapps': ['DappRadar'], 'dapp_categories': ['DappRadar'], 'dapp_chains': ['DappRadar'], 'dapp_metrics': ['DappRadar'], 'defi_chains': ['DappRadar'], 'tokens': ['DappRadar'], 'fees': ['Cryptostats']}, 'crypto/disc', '/')

Question: What is the value of ' new_key ' in line '22' after '1' th iteration when 'flatten({'top': ['CoinGecko', 'CoinMarketCap'], 'trending': ['CoinGecko'], 'gainers': ['CoinGecko'], 'losers': ['CoinGecko'], 'search': ['CoinPaprika'], 'nft_mktp_chains': ['DappRadar'], 'nft_mktp': ['DappRadar'], 'dapps': ['DappRadar'], 'dapp_categories': ['DappRadar'], 'dapp_chains': ['DappRadar'], 'dapp_metrics': ['DappRadar'], 'defi_chains': ['DappRadar'], 'tokens': ['DappRadar'], 'fees': ['Cryptostats']}, 'crypto/disc', '/')' is executed?

Answer: 'crypto/disc/top'


1: def _test_grad_nd(n, ndim):
2:     coords = [np.arange(n)] * ndim
3:     xc = np.meshgrid(*coords, indexing="ij")
4:
5:     # u = sum_i(xc[i]**2)
6:     u = reduce(lambda x,y: x+y**2, xc, 0.0)
7:     ucopy = np.copy(u)
8:
9:     # check the gradient values
10:     slices = tuple([slice(1,-1,None)] * ndim)
11:     for i in range(ndim):
12:         assert grad(u, axis=i) == pytest.approx(2*xc[i][slices])
13:
14:     # check if u is unchanged
15:     assert np.all(u == ucopy)
16:
17: _test_grad_nd(92, 1)

Question: What is the value of ' @py_assert7 ' in line '12' after '2' th iteration when '_test_grad_nd(92, 1)' is executed?

Answer: None


1: def _test_grad2_nd(n, ndim):
2:     coords = [np.arange(n)] * ndim
3:     xc = np.meshgrid(*coords, indexing="ij")
4:
5:     # u = sum_i(xc[i]**2)
6:     u = reduce(lambda x,y: x+y**2, xc, 0.0)
7:     ucopy = np.copy(u)
8:
9:     # check the gradient values
10:     gu = np.zeros(tuple([n-2]*ndim))
11:     gu2 = gu + 2.0
12:     for i in range(ndim):
13:         for j in range(ndim):
14:             if i == j:
15:                 assert grad2(u, axes=(i,j)) == pytest.approx(gu2)
16:             else:
17:                 assert grad2(u, axes=(i,j)) == pytest.approx(gu)
18:
19:     # check if u is unchanged
20:     assert np.all(u == ucopy)
21:
22: _test_grad2_nd(32, 1)

Question: What is the value of ' @py_assert11 ' in line '15' after '4' th iteration when '_test_grad2_nd(32, 1)' is executed?

Answer: None


1: def _makeComplementTable(complementData):
2:         """
3:         Make a sequence complement table.
4:
5:         @param complementData: A C{dict} whose keys and values are strings of
6:             length one. A key, value pair indicates a substitution that should
7:             be performed during complementation.
8:         @return: A 256 character string that can be used as a translation table
9:             by the C{translate} method of a Python string.
10:         """
11:         table = list(range(256))
12:         for _from, to in complementData.items():
13:             table[ord(_from[0].lower())] = ord(to[0].lower())
14:             table[ord(_from[0].upper())] = ord(to[0].upper())
15:         return ''.join(map(chr, table))
16:
17: _makeComplementTable({'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A', 'M': 'K', 'R': 'Y', 'W': 'W', 'S': 'S', 'Y': 'R', 'K': 'M', 'V': 'B', 'H': 'D', 'D': 'H', 'B': 'V', 'X': 'X', 'N': 'N'})

Question: What is the value of ' table ' in line '13' after '2' th iteration when '_makeComplementTable({'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A', 'M': 'K', 'R': 'Y', 'W': 'W', 'S': 'S', 'Y': 'R', 'K': 'M', 'V': 'B', 'H': 'D', 'D': 'H', 'B': 'V', 'X': 'X', 'N': 'N'})' is executed?

Answer: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 84, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 116, 98, 103, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255]


def test_audioclip_stereo_max_volume(nchannels, channel_muted):
    def make_frame(t): # [STATE] make_frame = <function test_audioclip_stereo_max_volume.<locals>.make_frame at 0x7f8c02a8e670> [/STATE]
        frame = []
        # build channels (one of each pair muted)
        for i in range(int(nchannels / 2)):
            if channel_muted == "left":
                # if muted channel is left, [0, sound, 0, sound...]
                frame.append(np.sin(t * 0))
                frame.append(np.sin(440 * 2 * np.pi * t))
            else:
                # if muted channel is right, [sound, 0, sound, 0...]
                frame.append(np.sin(440 * 2 * np.pi * t))
                frame.append(np.sin(t * 0))
        return np.array(frame).T

    clip = AudioClip(make_frame, fps=44100, duration=1) # [STATE] clip = {start=0, end=1, duration=1, memoize=False, memoized_t=None, memoized_frame=None, fps=44100, nchannels=2} [/STATE]
    max_volume = clip.max_volume(stereo=True) # [STATE] max_volume = array([0.        , 0.99999975]) [/STATE]
    # if `stereo == True`, `AudioClip.max_volume` returns a Numpy array`
    assert isinstance(max_volume, np.ndarray) # [STATE] @py_assert3 = None [/STATE] # [STATE] @py_assert5 = None [/STATE]
    assert len(max_volume) == nchannels # [STATE] @py_assert2 = None [/STATE] # [STATE] @py_assert4 = None [/STATE]

    # check channels muted and with sound
    for i, channel_max_volume in enumerate(max_volume): #  [STATE] i = 0 [/STATE] [STATE] channel_max_volume = 0.0 [/STATE] [STATE] i = 1 [/STATE] [STATE] channel_max_volume = 0.999999746257887 [/STATE]
        if i % 2 == 0:
            if channel_muted == "left":
                assert channel_max_volume == 0 # [STATE] @py_assert1 = None [/STATE]
            else:
                assert channel_max_volume > 0
        else:
            if channel_muted == "right":
                assert channel_max_volume == 0
            else:
                assert channel_max_volume > 0

test_audioclip_stereo_max_volume(2, 'left')

1: def test_audioclip_stereo_max_volume(nchannels, channel_muted):
2:     def make_frame(t):
3:         frame = []
4:         # build channels (one of each pair muted)
5:         for i in range(int(nchannels / 2)):
6:             if channel_muted == "left":
7:                 # if muted channel is left, [0, sound, 0, sound...]
8:                 frame.append(np.sin(t * 0))
9:                 frame.append(np.sin(440 * 2 * np.pi * t))
10:             else:
11:                 # if muted channel is right, [sound, 0, sound, 0...]
12:                 frame.append(np.sin(440 * 2 * np.pi * t))
13:                 frame.append(np.sin(t * 0))
14:         return np.array(frame).T
15:
16:     clip = AudioClip(make_frame, fps=44100, duration=1)
17:     max_volume = clip.max_volume(stereo=True)
18:     # if `stereo == True`, `AudioClip.max_volume` returns a Numpy array`
19:     assert isinstance(max_volume, np.ndarray)
20:     assert len(max_volume) == nchannels
21:
22:     # check channels muted and with sound
23:     for i, channel_max_volume in enumerate(max_volume):
24:         if i % 2 == 0:
25:             if channel_muted == "left":
26:                 assert channel_max_volume == 0
27:             else:
28:                 assert channel_max_volume > 0
29:         else:
30:             if channel_muted == "right":
31:                 assert channel_max_volume == 0
32:             else:
33:                 assert channel_max_volume > 0
34:
35: test_audioclip_stereo_max_volume(2, 'left')

Question: What is the value of ' table ' in line '13' after '2' th iteration when 'test_audioclip_stereo_max_volume(2, 'left')' is executed?

Answer: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 84, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 116, 98, 103, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255]


def find_extension(codec):
    """Returns the correspondent file extension for a codec.

    Parameters
    ----------

    codec : str
      Video or audio codec name.
    """
    if codec in extensions_dict:
        # codec is already the extension
        return codec

    for ext, infos in extensions_dict.items(): #  [STATE] ext = 'mp4' [/STATE] [STATE] infos = {'type': 'video', 'codec': ['libx264', 'libmpeg4', 'aac']} [/STATE] [STATE] ext = 'mkv' [/STATE] [STATE] ext = 'ogv' [/STATE] [STATE] infos = {'type': 'video', 'codec': ['libtheora']} [/STATE] [STATE] ext = 'webm' [/STATE] [STATE] infos = {'type': 'video', 'codec': ['libvpx']} [/STATE] [STATE] ext = 'avi' [/STATE] [STATE] infos = {'type': 'video'} [/STATE] [STATE] ext = 'mov' [/STATE] [STATE] ext = 'ogg' [/STATE] [STATE] infos = {'type': 'audio', 'codec': ['libvorbis']} [/STATE] [STATE] ext = 'mp3' [/STATE] [STATE] infos = {'type': 'audio', 'codec': ['libmp3lame']} [/STATE]
        if codec in infos.get("codec", []):
            return ext
    raise ValueError(
        "The audio_codec you chose is unknown by MoviePy. "
        "You should report this. In the meantime, you can "
        "specify a temp_audiofile with the right extension "
        "in write_videofile."
    )

find_extension('libmp3lame')

1: def find_extension(codec):
2:     """Returns the correspondent file extension for a codec.
3:
4:     Parameters
5:     ----------
6:
7:     codec : str
8:       Video or audio codec name.
9:     """
10:     if codec in extensions_dict:
11:         # codec is already the extension
12:         return codec
13:
14:     for ext, infos in extensions_dict.items():
15:         if codec in infos.get("codec", []):
16:             return ext
17:     raise ValueError(
18:         "The audio_codec you chose is unknown by MoviePy. "
19:         "You should report this. In the meantime, you can "
20:         "specify a temp_audiofile with the right extension "
21:         "in write_videofile."
22:     )
23:
24: find_extension('libmp3lame')

Question: What is the value of ' ext ' in line '14' after '6' th iteration when 'find_extension('libmp3lame')' is executed?

Answer: 'webm'


def version_compare(v1, v2):
    """Returns -1 if v1 is older than v2, 0 if v1 == v2, and +1 if v1 > v2."""

    arr1 = v1.split(".") # [STATE] arr1 = ['3', '8', '18'] [/STATE]
    arr2 = v2.split(".") # [STATE] arr2 = ['3', '8', '27'] [/STATE]
    n = len(arr1) # [STATE] n = 3 [/STATE]
    m = len(arr2) # [STATE] m = 3 [/STATE]

    # converts to integer from string
    arr1 = [int(i) for i in arr1] # [STATE] arr1 = [3, 8, 18] [/STATE]
    arr2 = [int(i) for i in arr2] # [STATE] arr2 = [3, 8, 27] [/STATE]

    # compares which list is bigger and fills
    # smaller list with zero (for unequal delimeters)
    if n > m:
        for i in range(m, n):
            arr2.append(0)
    elif m > n:
        for i in range(n, m):
            arr1.append(0)

    # returns 1 if version 1 is bigger and -1 if
    # version 2 is bigger and 0 if equal
    for i in range(len(arr1)): #  [STATE] i = 0 [/STATE] [STATE] i = 1 [/STATE] [STATE] i = 2 [/STATE]
        if arr1[i] > arr2[i]:
            return 1
        elif arr2[i] > arr1[i]:
            return -1
    return 0

version_compare('3.8.18', '3.8.27')

1: def version_compare(v1, v2):
2:     """Returns -1 if v1 is older than v2, 0 if v1 == v2, and +1 if v1 > v2."""
3:
4:     arr1 = v1.split(".")
5:     arr2 = v2.split(".")
6:     n = len(arr1)
7:     m = len(arr2)
8:
9:     # converts to integer from string
10:     arr1 = [int(i) for i in arr1]
11:     arr2 = [int(i) for i in arr2]
12:
13:     # compares which list is bigger and fills
14:     # smaller list with zero (for unequal delimeters)
15:     if n > m:
16:         for i in range(m, n):
17:             arr2.append(0)
18:     elif m > n:
19:         for i in range(n, m):
20:             arr1.append(0)
21:
22:     # returns 1 if version 1 is bigger and -1 if
23:     # version 2 is bigger and 0 if equal
24:     for i in range(len(arr1)):
25:         if arr1[i] > arr2[i]:
26:             return 1
27:         elif arr2[i] > arr1[i]:
28:             return -1
29:     return 0
30:
31: version_compare('3.8.18', '3.8.27')

Question: What is the value of ' ext ' in line '14' after '6' th iteration when 'version_compare('3.8.18', '3.8.27')' is executed?

Answer: 'webm'


def _validate_htype_overwrites(htype: str, htype_overwrite: dict):
    """Raises errors if ``htype_overwrite`` has invalid keys or was missing required values."""

    defaults = HTYPE_CONFIGURATIONS[htype] # [STATE] defaults = {'dtype': None, 'sample_compression': None, 'chunk_compression': None, 'typestr': None, 'max_chunk_size': None, 'tiling_threshold': None, 'is_sequence': False, 'is_link': False, 'hidden': False, 'links': None, 'verify': False} [/STATE]

    for key, value in htype_overwrite.items(): #  [STATE] key = 'sample_compression' [/STATE] [STATE] value = 'unspecified' [/STATE] [STATE] key = 'chunk_compression' [/STATE] [STATE] key = 'dtype' [/STATE] [STATE] value = 'int64' [/STATE] [STATE] key = 'hidden' [/STATE] [STATE] value = True [/STATE] [STATE] key = 'max_chunk_size' [/STATE] [STATE] value = 4000000 [/STATE] [STATE] key = 'is_sequence' [/STATE] [STATE] value = False [/STATE] [STATE] key = 'is_link' [/STATE] [STATE] key = 'verify' [/STATE]
        if key not in defaults:
            raise TensorMetaInvalidHtypeOverwriteKey(htype, key, list(defaults.keys()))

        if isinstance(value, str) and value == UNSPECIFIED:
            if defaults[key] == REQUIRE_USER_SPECIFICATION:
                raise TensorMetaMissingRequiredValue(htype, key)

    sc = htype_overwrite["sample_compression"] # [STATE] sc = 'unspecified' [/STATE]
    cc = htype_overwrite["chunk_compression"] # [STATE] cc = 'unspecified' [/STATE]
    compr = sc if cc in (None, UNSPECIFIED) else cc # [STATE] compr = 'unspecified' [/STATE]
    actual_htype = f"link[{htype}]" if htype_overwrite["is_link"] else htype # [STATE] actual_htype = 'generic' [/STATE]
    if htype.startswith("image") and sc == UNSPECIFIED and cc == UNSPECIFIED:
        raise TensorMetaMissingRequiredValue(
            actual_htype, ["chunk_compression", "sample_compression"]  # type: ignore
        )
    if htype in ("audio", "video", "point_cloud", "mesh", "nifti"):
        if cc not in (UNSPECIFIED, None):
            raise UnsupportedCompressionError("Chunk compression", htype=htype)
        elif sc == UNSPECIFIED:
            raise TensorMetaMissingRequiredValue(
                actual_htype, "sample_compression"  # type: ignore
            )
    supported_compressions = HTYPE_SUPPORTED_COMPRESSIONS.get(htype) # [STATE] supported_compressions = None [/STATE]
    if (
        compr
        and compr != UNSPECIFIED
        and supported_compressions
        and compr not in supported_compressions
    ):
        raise UnsupportedCompressionError(compr, htype=htype)

_validate_htype_overwrites('generic', {'sample_compression': 'unspecified', 'chunk_compression': 'unspecified', 'dtype': 'int64', 'hidden': True, 'max_chunk_size': 4000000, 'is_sequence': False, 'is_link': False, 'verify': True})

1: def _validate_htype_overwrites(htype: str, htype_overwrite: dict):
2:     """Raises errors if ``htype_overwrite`` has invalid keys or was missing required values."""
3:
4:     defaults = HTYPE_CONFIGURATIONS[htype]
5:
6:     for key, value in htype_overwrite.items():
7:         if key not in defaults:
8:             raise TensorMetaInvalidHtypeOverwriteKey(htype, key, list(defaults.keys()))
9:
10:         if isinstance(value, str) and value == UNSPECIFIED:
11:             if defaults[key] == REQUIRE_USER_SPECIFICATION:
12:                 raise TensorMetaMissingRequiredValue(htype, key)
13:
14:     sc = htype_overwrite["sample_compression"]
15:     cc = htype_overwrite["chunk_compression"]
16:     compr = sc if cc in (None, UNSPECIFIED) else cc
17:     actual_htype = f"link[{htype}]" if htype_overwrite["is_link"] else htype
18:     if htype.startswith("image") and sc == UNSPECIFIED and cc == UNSPECIFIED:
19:         raise TensorMetaMissingRequiredValue(
20:             actual_htype, ["chunk_compression", "sample_compression"]  # type: ignore
21:         )
22:     if htype in ("audio", "video", "point_cloud", "mesh", "nifti"):
23:         if cc not in (UNSPECIFIED, None):
24:             raise UnsupportedCompressionError("Chunk compression", htype=htype)
25:         elif sc == UNSPECIFIED:
26:             raise TensorMetaMissingRequiredValue(
27:                 actual_htype, "sample_compression"  # type: ignore
28:             )
29:     supported_compressions = HTYPE_SUPPORTED_COMPRESSIONS.get(htype)
30:     if (
31:         compr
32:         and compr != UNSPECIFIED
33:         and supported_compressions
34:         and compr not in supported_compressions
35:     ):
36:         raise UnsupportedCompressionError(compr, htype=htype)
37:
38: _validate_htype_overwrites('generic', {'sample_compression': 'unspecified', 'chunk_compression': 'unspecified', 'dtype': 'int64', 'hidden': True, 'max_chunk_size': 4000000, 'is_sequence': False, 'is_link': False, 'verify': True})

Question: What is the value of ' key ' in line '6' after '4' th iteration when '_validate_htype_overwrites('generic', {'sample_compression': 'unspecified', 'chunk_compression': 'unspecified', 'dtype': 'int64', 'hidden': True, 'max_chunk_size': 4000000, 'is_sequence': False, 'is_link': False, 'verify': True})' is executed?

Answer: 'dtype'


def _replace_unspecified_values(htype: str, htype_overwrite: dict):
    """Replaces ``UNSPECIFIED`` values in ``htype_overwrite`` with the ``htype``'s defaults."""

    defaults = HTYPE_CONFIGURATIONS[htype] # [STATE] defaults = {'dtype': None, 'sample_compression': None, 'chunk_compression': None, 'typestr': None, 'max_chunk_size': None, 'tiling_threshold': None, 'is_sequence': False, 'is_link': False, 'hidden': False, 'links': None, 'verify': False} [/STATE]

    for k, v in htype_overwrite.items(): #  [STATE] k = 'sample_compression' [/STATE] [STATE] v = 'unspecified' [/STATE] [STATE] k = 'chunk_compression' [/STATE] [STATE] k = 'dtype' [/STATE] [STATE] v = 'int64' [/STATE] [STATE] k = 'hidden' [/STATE] [STATE] v = True [/STATE] [STATE] k = 'max_chunk_size' [/STATE] [STATE] v = 4000000 [/STATE] [STATE] k = 'is_sequence' [/STATE] [STATE] v = False [/STATE] [STATE] k = 'is_link' [/STATE] [STATE] k = 'verify' [/STATE]
        if isinstance(v, str) and v == UNSPECIFIED:
            htype_overwrite[k] = defaults[k] #  [STATE] htype_overwrite = {'sample_compression': None, 'chunk_compression': 'unspecified', 'dtype': 'int64', 'hidden': True, 'max_chunk_size': 4000000, 'is_sequence': False, 'is_link': False, 'verify': True} [/STATE] [STATE] htype_overwrite = {'sample_compression': None, 'chunk_compression': None, 'dtype': 'int64', 'hidden': True, 'max_chunk_size': 4000000, 'is_sequence': False, 'is_link': False, 'verify': True} [/STATE]

    if htype in ("json", "list", "text", "intrinsics") and not htype_overwrite["dtype"]:
        htype_overwrite["dtype"] = HTYPE_CONFIGURATIONS[htype]["dtype"]

_replace_unspecified_values('generic', {'sample_compression': 'unspecified', 'chunk_compression': 'unspecified', 'dtype': 'int64', 'hidden': True, 'max_chunk_size': 4000000, 'is_sequence': False, 'is_link': False, 'verify': True})

1: def _replace_unspecified_values(htype: str, htype_overwrite: dict):
2:     """Replaces ``UNSPECIFIED`` values in ``htype_overwrite`` with the ``htype``'s defaults."""
3:
4:     defaults = HTYPE_CONFIGURATIONS[htype]
5:
6:     for k, v in htype_overwrite.items():
7:         if isinstance(v, str) and v == UNSPECIFIED:
8:             htype_overwrite[k] = defaults[k]
9:
10:     if htype in ("json", "list", "text", "intrinsics") and not htype_overwrite["dtype"]:
11:         htype_overwrite["dtype"] = HTYPE_CONFIGURATIONS[htype]["dtype"]
12:
13: _replace_unspecified_values('generic', {'sample_compression': 'unspecified', 'chunk_compression': 'unspecified', 'dtype': 'int64', 'hidden': True, 'max_chunk_size': 4000000, 'is_sequence': False, 'is_link': False, 'verify': True})

Question: What is the value of ' htype_overwrite ' in line '8' after '2' th iteration when '_replace_unspecified_values('generic', {'sample_compression': 'unspecified', 'chunk_compression': 'unspecified', 'dtype': 'int64', 'hidden': True, 'max_chunk_size': 4000000, 'is_sequence': False, 'is_link': False, 'verify': True})' is executed?

Answer: {'sample_compression': None, 'chunk_compression': None, 'dtype': 'int64', 'hidden': True, 'max_chunk_size': 4000000, 'is_sequence': False, 'is_link': False, 'verify': True}


def move_is_sublist(letter_list_1, letter_list_2):
    letter_counter_1 = collections.Counter(letter_list_1) # [STATE] letter_counter_1 = Counter({1: 1, 2: 1, 3: 1}) [/STATE]
    letter_counter_2 = collections.Counter(letter_list_2) # [STATE] letter_counter_2 = Counter({1: 1, 2: 1, 3: 1, 4: 1}) [/STATE]
    for letter, cardinality in letter_counter_1.items(): #  [STATE] letter = 1 [/STATE] [STATE] cardinality = 1 [/STATE] [STATE] letter = 2 [/STATE] [STATE] letter = 3 [/STATE]
        if cardinality > letter_counter_2[letter]:
            # print('Not enough {} tiles in rack.'.format(letter))
            return False

    return True

move_is_sublist([1, 2, 3], [1, 2, 3, 4])

1: def move_is_sublist(letter_list_1, letter_list_2):
2:     letter_counter_1 = collections.Counter(letter_list_1)
3:     letter_counter_2 = collections.Counter(letter_list_2)
4:     for letter, cardinality in letter_counter_1.items():
5:         if cardinality > letter_counter_2[letter]:
6:             # print('Not enough {} tiles in rack.'.format(letter))
7:             return False
8:
9:     return True
10:
11: move_is_sublist([1, 2, 3], [1, 2, 3, 4])

Question: What is the value of ' letter ' in line '4' after '1' th iteration when 'move_is_sublist([1, 2, 3], [1, 2, 3, 4])' is executed?

Answer: 1


def get_word_letter_location_set(word, start_location, is_vertical_move):
    letter_location_set = set() # [STATE] letter_location_set = set() [/STATE]
    next_location_func = get_next_location_function( # [STATE] next_location_func = <function get_next_location_function.<locals>.<lambda> at 0x7feb6dd68f70> [/STATE]
        use_positive_seek=True,
        use_vertical_words=is_vertical_move
    )

    current_location = start_location # [STATE] current_location = ('h', 8) [/STATE]
    word_iterator = iter(word) # [STATE] word_iterator = REPR FAILED [/STATE]
    for character in word_iterator: #  [STATE] character = 'B' [/STATE] [STATE] character = 'A' [/STATE] [STATE] character = 'K' [/STATE] [STATE] character = 'E' [/STATE] [STATE] character = 'R' [/STATE]
        if character == '(':  # characters in parenthesis are existing tiles
            character = next(word_iterator, None)
            while character != ')':
                current_location = next_location_func(current_location)
                character = next(word_iterator, None)

            character = next(word_iterator, None)

        if character:
            letter_location_set.add((character, current_location)) #  [STATE] letter_location_set = {('B', ('h', 8))} [/STATE] [STATE] letter_location_set = {('B', ('h', 8)), ('A', ('i', 8))} [/STATE] [STATE] letter_location_set = {('K', ('j', 8)), ('B', ('h', 8)), ('A', ('i', 8))} [/STATE] [STATE] letter_location_set = {('K', ('j', 8)), ('B', ('h', 8)), ('E', ('k', 8)), ('A', ('i', 8))} [/STATE] [STATE] letter_location_set = {('K', ('j', 8)), ('B', ('h', 8)), ('A', ('i', 8)), ('E', ('k', 8)), ('R', ('l', 8))} [/STATE]
            current_location = next_location_func(current_location) #  [STATE] current_location = ('i', 8) [/STATE] [STATE] current_location = ('j', 8) [/STATE] [STATE] current_location = ('k', 8) [/STATE] [STATE] current_location = ('l', 8) [/STATE] [STATE] current_location = ('m', 8) [/STATE]

    return letter_location_set

get_word_letter_location_set('BAKER', ('h', 8), False)

1: def get_word_letter_location_set(word, start_location, is_vertical_move):
2:     letter_location_set = set()
3:     next_location_func = get_next_location_function(
4:         use_positive_seek=True,
5:         use_vertical_words=is_vertical_move
6:     )
7:
8:     current_location = start_location
9:     word_iterator = iter(word)
10:     for character in word_iterator:
11:         if character == '(':  # characters in parenthesis are existing tiles
12:             character = next(word_iterator, None)
13:             while character != ')':
14:                 current_location = next_location_func(current_location)
15:                 character = next(word_iterator, None)
16:
17:             character = next(word_iterator, None)
18:
19:         if character:
20:             letter_location_set.add((character, current_location))
21:             current_location = next_location_func(current_location)
22:
23:     return letter_location_set
24:
25: get_word_letter_location_set('BAKER', ('h', 8), False)

Question: What is the value of ' letter_location_set ' in line '20' after '5' th iteration when 'get_word_letter_location_set('BAKER', ('h', 8), False)' is executed?

Answer: {('K', ('j', 8)), ('B', ('h', 8)), ('A', ('i', 8)), ('E', ('k', 8)), ('R', ('l', 8))}


def move_is_not_out_of_bounds(location_set):
    for location in location_set: #  [STATE] location = ('j', 8) [/STATE] [STATE] location = ('l', 8) [/STATE] [STATE] location = ('h', 8) [/STATE] [STATE] location = ('i', 8) [/STATE] [STATE] location = ('k', 8) [/STATE]
        if location_is_out_of_bounds(location):
            # print('Move location {} is out of bounds'.format(location))
            return False

    return True

move_is_not_out_of_bounds({('j', 8), ('l', 8), ('h', 8), ('i', 8), ('k', 8)})

1: def move_is_not_out_of_bounds(location_set):
2:     for location in location_set:
3:         if location_is_out_of_bounds(location):
4:             # print('Move location {} is out of bounds'.format(location))
5:             return False
6:
7:     return True
8:
9: move_is_not_out_of_bounds({('j', 8), ('l', 8), ('h', 8), ('i', 8), ('k', 8)})

Question: What is the value of ' location ' in line '2' after '5' th iteration when 'move_is_not_out_of_bounds({('j', 8), ('l', 8), ('h', 8), ('i', 8), ('k', 8)})' is executed?

Answer: ('k', 8)


def find_prev_keyword(sql):
    """ Find the last sql keyword in an SQL statement

    Returns the value of the last keyword, and the text of the query with
    everything after the last keyword stripped
    """
    if not sql.strip():
        return None, ''

    parsed = sqlparse.parse(sql)[0] # [STATE] parsed = <Statement ',' at 0x7F95CFCE60B0> [/STATE]
    flattened = list(parsed.flatten()) # [STATE] flattened = [<Punctuation ',' at 0x7F95CFC8FC40>] [/STATE]

    logical_operators = ('AND', 'OR', 'NOT', 'BETWEEN') # [STATE] logical_operators = ('AND', 'OR', 'NOT', 'BETWEEN') [/STATE]

    for t in reversed(flattened): #  [STATE] t = <Punctuation ',' at 0x7F95CFC8FC40> [/STATE]
        if t.value == '(' or (t.is_keyword and (
                              t.value.upper() not in logical_operators)):
            # Find the location of token t in the original parsed statement
            # We can't use parsed.token_index(t) because t may be a child token
            # inside a TokenList, in which case token_index thows an error
            # Minimal example:
            #   p = sqlparse.parse('select * from foo where bar')
            #   t = list(p.flatten())[-3]  # The "Where" token
            #   p.token_index(t)  # Throws ValueError: not in list
            idx = flattened.index(t)

            # Combine the string values of all tokens in the original list
            # up to and including the target keyword token t, to produce a
            # query string with everything after the keyword token removed
            text = ''.join(tok.value for tok in flattened[:idx+1])
            return t, text

    return None, ''

find_prev_keyword(',')

1: def find_prev_keyword(sql):
2:     """ Find the last sql keyword in an SQL statement
3:
4:     Returns the value of the last keyword, and the text of the query with
5:     everything after the last keyword stripped
6:     """
7:     if not sql.strip():
8:         return None, ''
9:
10:     parsed = sqlparse.parse(sql)[0]
11:     flattened = list(parsed.flatten())
12:
13:     logical_operators = ('AND', 'OR', 'NOT', 'BETWEEN')
14:
15:     for t in reversed(flattened):
16:         if t.value == '(' or (t.is_keyword and (
17:                               t.value.upper() not in logical_operators)):
18:             # Find the location of token t in the original parsed statement
19:             # We can't use parsed.token_index(t) because t may be a child token
20:             # inside a TokenList, in which case token_index thows an error
21:             # Minimal example:
22:             #   p = sqlparse.parse('select * from foo where bar')
23:             #   t = list(p.flatten())[-3]  # The "Where" token
24:             #   p.token_index(t)  # Throws ValueError: not in list
25:             idx = flattened.index(t)
26:
27:             # Combine the string values of all tokens in the original list
28:             # up to and including the target keyword token t, to produce a
29:             # query string with everything after the keyword token removed
30:             text = ''.join(tok.value for tok in flattened[:idx+1])
31:             return t, text
32:
33:     return None, ''
34:
35: find_prev_keyword(',')

Question: What is the value of ' t ' in line '15' after '1' th iteration when 'find_prev_keyword(',')' is executed?

Answer: <Punctuation ',' at 0x7F95CFC8FC40>


def format_uptime(uptime_in_seconds):
    """Format number of seconds into human-readable string.

    :param uptime_in_seconds: The server uptime in seconds.
    :returns: A human-readable string representing the uptime.

    >>> uptime = format_uptime('56892')
    >>> print(uptime)
    15 hours 48 min 12 sec
    """

    m, s = divmod(int(uptime_in_seconds), 60) # [STATE] m = 0 [/STATE] # [STATE] s = 59 [/STATE]
    h, m = divmod(m, 60) # [STATE] h = 0 [/STATE]
    d, h = divmod(h, 24) # [STATE] d = 0 [/STATE]

    uptime_values = [] # [STATE] uptime_values = [] [/STATE]

    for value, unit in ((d, 'days'), (h, 'hours'), (m, 'min'), (s, 'sec')): #  [STATE] value = 0 [/STATE] [STATE] unit = 'days' [/STATE] [STATE] unit = 'hours' [/STATE] [STATE] unit = 'min' [/STATE] [STATE] value = 59 [/STATE] [STATE] unit = 'sec' [/STATE]
        if value == 0 and not uptime_values:
            # Don't include a value/unit if the unit isn't applicable to
            # the uptime. E.g. don't do 0 days 0 hours 1 min 30 sec.
            continue
        elif value == 1 and unit.endswith('s'):
            # Remove the "s" if the unit is singular.
            unit = unit[:-1]
        uptime_values.append('{0} {1}'.format(value, unit)) # [STATE] uptime_values = ['59 sec'] [/STATE]

    uptime = ' '.join(uptime_values) # [STATE] uptime = '59 sec' [/STATE]
    return uptime

format_uptime(59)

1: def format_uptime(uptime_in_seconds):
2:     """Format number of seconds into human-readable string.
3:
4:     :param uptime_in_seconds: The server uptime in seconds.
5:     :returns: A human-readable string representing the uptime.
6:
7:     >>> uptime = format_uptime('56892')
8:     >>> print(uptime)
9:     15 hours 48 min 12 sec
10:     """
11:
12:     m, s = divmod(int(uptime_in_seconds), 60)
13:     h, m = divmod(m, 60)
14:     d, h = divmod(h, 24)
15:
16:     uptime_values = []
17:
18:     for value, unit in ((d, 'days'), (h, 'hours'), (m, 'min'), (s, 'sec')):
19:         if value == 0 and not uptime_values:
20:             # Don't include a value/unit if the unit isn't applicable to
21:             # the uptime. E.g. don't do 0 days 0 hours 1 min 30 sec.
22:             continue
23:         elif value == 1 and unit.endswith('s'):
24:             # Remove the "s" if the unit is singular.
25:             unit = unit[:-1]
26:         uptime_values.append('{0} {1}'.format(value, unit))
27:
28:     uptime = ' '.join(uptime_values)
29:     return uptime
30:
31: format_uptime(59)

Question: What is the value of ' uptime_values ' in line '26' after '1' th iteration when 'format_uptime(59)' is executed?

Answer: ['59 sec']


def contains_nan(stack: MutableSequence[NumberOrArray]) -> bool:
    for item in stack: #  [STATE] item = -2 [/STATE]
        try:
            if math.isnan(item):
                return True
        except TypeError:
            pass
    return False

contains_nan([-2])

1: def contains_nan(stack: MutableSequence[NumberOrArray]) -> bool:
2:     for item in stack:
3:         try:
4:             if math.isnan(item):
5:                 return True
6:         except TypeError:
7:             pass
8:     return False
9:
10: contains_nan([-2])

Question: What is the value of ' item ' in line '2' after '1' th iteration when 'contains_nan([-2])' is executed?

Answer: -2


def contains_array(stack: MutableSequence[NumberOrArray]) -> bool:
    for item in stack: #  [STATE] item = -2 [/STATE]
        if isinstance(item, np.ndarray):
            return True
    return False

contains_array([-2])

1: def contains_array(stack: MutableSequence[NumberOrArray]) -> bool:
2:     for item in stack:
3:         if isinstance(item, np.ndarray):
4:             return True
5:     return False
6:
7: contains_array([-2])

Question: What is the value of ' item ' in line '2' after '1' th iteration when 'contains_array([-2])' is executed?

Answer: -2


def import_all_modules(root: str, base_module: str) -> List[str]:
    modules: List[str] = [] # [STATE] modules = [] [/STATE]
    for file in os.listdir(root): #  [STATE] file = 'feature_maps' [/STATE] [STATE] file = 'global_tokens.py' [/STATE] [STATE] file = 'lambda_layer.py' [/STATE] [STATE] file = 'pooling.py' [/STATE] [STATE] file = 'core.py' [/STATE] [STATE] file = 'visual.py' [/STATE] [STATE] file = 'nystrom.py' [/STATE] [STATE] file = 'attention_patterns.py' [/STATE] [STATE] file = '_sputnik_sparse.py' [/STATE] [STATE] file = 'sparsity_config.py' [/STATE] [STATE] file = 'scaled_dot_product.py' [/STATE] [STATE] file = 'compositional.py' [/STATE] [STATE] file = 'attention_mask.py' [/STATE] [STATE] file = 'local.py' [/STATE] [STATE] file = '__pycache__' [/STATE] [STATE] file = 'utils.py' [/STATE] [STATE] file = 'linformer.py' [/STATE] [STATE] file = '__init__.py' [/STATE] [STATE] file = 'favor.py' [/STATE] [STATE] file = 'base.py' [/STATE] [STATE] file = 'random.py' [/STATE]
        if file.endswith((".py", ".pyc")) and not file.startswith("_"):
            module = file[: file.find(".py")] #  [STATE] module = 'global_tokens' [/STATE] [STATE] module = 'lambda_layer' [/STATE] [STATE] module = 'pooling' [/STATE] [STATE] module = 'core' [/STATE] [STATE] module = 'visual' [/STATE] [STATE] module = 'nystrom' [/STATE] [STATE] module = 'attention_patterns' [/STATE] [STATE] module = 'sparsity_config' [/STATE] [STATE] module = 'scaled_dot_product' [/STATE] [STATE] module = 'compositional' [/STATE] [STATE] module = 'attention_mask' [/STATE] [STATE] module = 'local' [/STATE] [STATE] module = 'utils' [/STATE] [STATE] module = 'linformer' [/STATE] [STATE] module = 'favor' [/STATE] [STATE] module = 'base' [/STATE] [STATE] module = 'random' [/STATE] [STATE] module = 'blocksparse' [/STATE] [STATE] module = 'ortho' [/STATE] [STATE] module = 'fourier_mix' [/STATE]
            if module not in sys.modules:
                module_name = ".".join([base_module, module]) #  [STATE] module_name = 'xformers.components.attention.global_tokens' [/STATE] [STATE] module_name = 'xformers.components.attention.lambda_layer' [/STATE] [STATE] module_name = 'xformers.components.attention.pooling' [/STATE] [STATE] module_name = 'xformers.components.attention.core' [/STATE] [STATE] module_name = 'xformers.components.attention.visual' [/STATE] [STATE] module_name = 'xformers.components.attention.nystrom' [/STATE] [STATE] module_name = 'xformers.components.attention.attention_patterns' [/STATE] [STATE] module_name = 'xformers.components.attention.sparsity_config' [/STATE] [STATE] module_name = 'xformers.components.attention.scaled_dot_product' [/STATE] [STATE] module_name = 'xformers.components.attention.compositional' [/STATE] [STATE] module_name = 'xformers.components.attention.attention_mask' [/STATE] [STATE] module_name = 'xformers.components.attention.local' [/STATE] [STATE] module_name = 'xformers.components.attention.utils' [/STATE] [STATE] module_name = 'xformers.components.attention.linformer' [/STATE] [STATE] module_name = 'xformers.components.attention.favor' [/STATE] [STATE] module_name = 'xformers.components.attention.base' [/STATE] [STATE] module_name = 'xformers.components.attention.blocksparse' [/STATE] [STATE] module_name = 'xformers.components.attention.ortho' [/STATE] [STATE] module_name = 'xformers.components.attention.fourier_mix' [/STATE]
                importlib.import_module(module_name)
                modules.append(module_name) #  [STATE] modules = ['xformers.components.attention.global_tokens'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling', 'xformers.components.attention.core'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling', 'xformers.components.attention.core', 'xformers.components.attention.visual'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling', 'xformers.components.attention.core', 'xformers.components.attention.visual', 'xformers.components.attention.nystrom'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling', 'xformers.components.attention.core', 'xformers.components.attention.visual', 'xformers.components.attention.nystrom', 'xformers.components.attention.attention_patterns'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling', 'xformers.components.attention.core', 'xformers.components.attention.visual', 'xformers.components.attention.nystrom', 'xformers.components.attention.attention_patterns', 'xformers.components.attention.sparsity_config'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling', 'xformers.components.attention.core', 'xformers.components.attention.visual', 'xformers.components.attention.nystrom', 'xformers.components.attention.attention_patterns', 'xformers.components.attention.sparsity_config', 'xformers.components.attention.scaled_dot_product'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling', 'xformers.components.attention.core', 'xformers.components.attention.visual', 'xformers.components.attention.nystrom', 'xformers.components.attention.attention_patterns', 'xformers.components.attention.sparsity_config', 'xformers.components.attention.scaled_dot_product', 'xformers.components.attention.compositional'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling', 'xformers.components.attention.core', 'xformers.components.attention.visual', 'xformers.components.attention.nystrom', 'xformers.components.attention.attention_patterns', 'xformers.components.attention.sparsity_config', 'xformers.components.attention.scaled_dot_product', 'xformers.components.attention.compositional', 'xformers.components.attention.attention_mask'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling', 'xformers.components.attention.core', 'xformers.components.attention.visual', 'xformers.components.attention.nystrom', 'xformers.components.attention.attention_patterns', 'xformers.components.attention.sparsity_config', 'xformers.components.attention.scaled_dot_product', 'xformers.components.attention.compositional', 'xformers.components.attention.attention_mask', 'xformers.components.attention.local'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling', 'xformers.components.attention.core', 'xformers.components.attention.visual', 'xformers.components.attention.nystrom', 'xformers.components.attention.attention_patterns', 'xformers.components.attention.sparsity_config', 'xformers.components.attention.scaled_dot_product', 'xformers.components.attention.compositional', 'xformers.components.attention.attention_mask', 'xformers.components.attention.local', 'xformers.components.attention.utils'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling', 'xformers.components.attention.core', 'xformers.components.attention.visual', 'xformers.components.attention.nystrom', 'xformers.components.attention.attention_patterns', 'xformers.components.attention.sparsity_config', 'xformers.components.attention.scaled_dot_product', 'xformers.components.attention.compositional', 'xformers.components.attention.attention_mask', 'xformers.components.attention.local', 'xformers.components.attention.utils', 'xformers.components.attention.linformer'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling', 'xformers.components.attention.core', 'xformers.components.attention.visual', 'xformers.components.attention.nystrom', 'xformers.components.attention.attention_patterns', 'xformers.components.attention.sparsity_config', 'xformers.components.attention.scaled_dot_product', 'xformers.components.attention.compositional', 'xformers.components.attention.attention_mask', 'xformers.components.attention.local', 'xformers.components.attention.utils', 'xformers.components.attention.linformer', 'xformers.components.attention.favor'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling', 'xformers.components.attention.core', 'xformers.components.attention.visual', 'xformers.components.attention.nystrom', 'xformers.components.attention.attention_patterns', 'xformers.components.attention.sparsity_config', 'xformers.components.attention.scaled_dot_product', 'xformers.components.attention.compositional', 'xformers.components.attention.attention_mask', 'xformers.components.attention.local', 'xformers.components.attention.utils', 'xformers.components.attention.linformer', 'xformers.components.attention.favor', 'xformers.components.attention.base'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling', 'xformers.components.attention.core', 'xformers.components.attention.visual', 'xformers.components.attention.nystrom', 'xformers.components.attention.attention_patterns', 'xformers.components.attention.sparsity_config', 'xformers.components.attention.scaled_dot_product', 'xformers.components.attention.compositional', 'xformers.components.attention.attention_mask', 'xformers.components.attention.local', 'xformers.components.attention.utils', 'xformers.components.attention.linformer', 'xformers.components.attention.favor', 'xformers.components.attention.base', 'xformers.components.attention.blocksparse'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling', 'xformers.components.attention.core', 'xformers.components.attention.visual', 'xformers.components.attention.nystrom', 'xformers.components.attention.attention_patterns', 'xformers.components.attention.sparsity_config', 'xformers.components.attention.scaled_dot_product', 'xformers.components.attention.compositional', 'xformers.components.attention.attention_mask', 'xformers.components.attention.local', 'xformers.components.attention.utils', 'xformers.components.attention.linformer', 'xformers.components.attention.favor', 'xformers.components.attention.base', 'xformers.components.attention.blocksparse', 'xformers.components.attention.ortho'] [/STATE] [STATE] modules = ['xformers.components.attention.global_tokens', 'xformers.components.attention.lambda_layer', 'xformers.components.attention.pooling', 'xformers.components.attention.core', 'xformers.components.attention.visual', 'xformers.components.attention.nystrom', 'xformers.components.attention.attention_patterns', 'xformers.components.attention.sparsity_config', 'xformers.components.attention.scaled_dot_product', 'xformers.components.attention.compositional', 'xformers.components.attention.attention_mask', 'xformers.components.attention.local', 'xformers.components.attention.utils', 'xformers.components.attention.linformer', 'xformers.components.attention.favor', 'xformers.components.attention.base', 'xformers.components.attention.blocksparse', 'xformers.components.attention.ortho', 'xformers.components.attention.fourier_mix'] [/STATE]

    return modules

import_all_modules('/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/facebookresearch+xformers/facebookresearch+xformers/xformers/components/attention', 'xformers.components.attention')

1: def import_all_modules(root: str, base_module: str) -> List[str]:
2:     modules: List[str] = []
3:     for file in os.listdir(root):
4:         if file.endswith((".py", ".pyc")) and not file.startswith("_"):
5:             module = file[: file.find(".py")]
6:             if module not in sys.modules:
7:                 module_name = ".".join([base_module, module])
8:                 importlib.import_module(module_name)
9:                 modules.append(module_name)
10:
11:     return modules
12:
13: import_all_modules('/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/facebookresearch+xformers/facebookresearch+xformers/xformers/components/attention', 'xformers.components.attention')

Question: What is the value of ' module ' in line '5' after '14' th iteration when 'import_all_modules('/local/rcs/XXX/code/pytrace-collector/logs/self_collected/tried/facebookresearch+xformers/facebookresearch+xformers/xformers/components/attention', 'xformers.components.attention')' is executed?

Answer: 'linformer'


def expand_attention_types(attention_config, num_layers):
    """
    Expands an `attention_config` list in the following format:

        [
        [['attention_type_1', ..., `attention_type_n`], 12]
        ]

    to a flattened list of length `num_layers`.

    :param params_list:
    :return:
    """
    # if only strings are found in the config, we assume it's already expanded
    if all([isinstance(i, str) for i in attention_config]):
        return attention_config
    newlist = [] # [STATE] newlist = [] [/STATE]
    for item in attention_config: #  [STATE] item = [['global'], 2] [/STATE]
        # instead of specifying a number - we can specify 'all' to extend this pattern across all layers
        if item[1] == "all":
            assert num_layers % len(item[0]) == 0, (
                f"Number of layers ({num_layers}) is not divisible by the length "
                f"of pattern: {item[0]}"
            )
            return item[0] * (num_layers // len(item[0]))
        for _ in range(item[1]): #  [STATE] _ = 0 [/STATE] [STATE] _ = 1 [/STATE]
            newlist.extend(item[0]) #  [STATE] newlist = ['global'] [/STATE] [STATE] newlist = ['global', 'global'] [/STATE]
    return newlist

expand_attention_types([[['global'], 2]], 2)

1: def expand_attention_types(attention_config, num_layers):
2:     """
3:     Expands an `attention_config` list in the following format:
4:
5:         [
6:         [['attention_type_1', ..., `attention_type_n`], 12]
7:         ]
8:
9:     to a flattened list of length `num_layers`.
10:
11:     :param params_list:
12:     :return:
13:     """
14:     # if only strings are found in the config, we assume it's already expanded
15:     if all([isinstance(i, str) for i in attention_config]):
16:         return attention_config
17:     newlist = []
18:     for item in attention_config:
19:         # instead of specifying a number - we can specify 'all' to extend this pattern across all layers
20:         if item[1] == "all":
21:             assert num_layers % len(item[0]) == 0, (
22:                 f"Number of layers ({num_layers}) is not divisible by the length "
23:                 f"of pattern: {item[0]}"
24:             )
25:             return item[0] * (num_layers // len(item[0]))
26:         for _ in range(item[1]):
27:             newlist.extend(item[0])
28:     return newlist
29:
30: expand_attention_types([[['global'], 2]], 2)

Question: What is the value of ' newlist ' in line '27' after '1' th iteration when 'expand_attention_types([[['global'], 2]], 2)' is executed?

Answer: ['global']


def set_up_autotuning(encoded_config, overwrite_values):
        config = json.loads(base64.urlsafe_b64decode(encoded_config).decode("utf-8")) # [STATE] config = {'train_batch_size': 4, 'train_micro_batch_size_per_gpu': 4, 'optimizer': {'type': 'sm3', 'params': {}}, 'fp16': {'type': 'fp16', 'enabled': True}, 'zero_optimization': {'stage': 0, 'allgather_partitions': True, 'reduce_scatter': True, 'allgather_bucket_size': 500000000, 'overlap_comm': False, 'reduce_bucket_size': 500000000, 'contiguous_gradients': False}, 'wall_clock_breakdown': True, 'comms_logger': {'enabled': True, 'verbose': True, 'prof_all': True, 'debug': False}} [/STATE]
        overwrite_values = overwrite_values if overwrite_values else {}
        for tuning_param in AUTOTUNING_ARGS: #  [STATE] tuning_param = 'train_batch_size' [/STATE] [STATE] tuning_param = 'train_micro_batch_size_per_gpu' [/STATE] [STATE] tuning_param = 'gradient_accumulation_steps' [/STATE] [STATE] tuning_param = 'zero_optimization' [/STATE] [STATE] tuning_param = 'autotuning' [/STATE]
            # TODO: This is for autotuning specifically, may cause surprises for someone with a weird setup
            if tuning_param in config:
                overwrite_values[tuning_param] = config[tuning_param] #  [STATE] overwrite_values = {'train_iters': 32, 'train_batch_size': 4} [/STATE] [STATE] overwrite_values = {'train_iters': 32, 'train_batch_size': 4, 'train_micro_batch_size_per_gpu': 4} [/STATE] [STATE] overwrite_values = {'train_iters': 32, 'train_batch_size': 4, 'train_micro_batch_size_per_gpu': 4, 'zero_optimization': {'stage': 0, 'allgather_partitions': True, 'reduce_scatter': True, 'allgather_bucket_size': 500000000, 'overlap_comm': False, 'reduce_bucket_size': 500000000, 'contiguous_gradients': False}} [/STATE]
        return overwrite_values

set_up_autotuning('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', {'train_iters': 32})

1: def set_up_autotuning(encoded_config, overwrite_values):
2:         config = json.loads(base64.urlsafe_b64decode(encoded_config).decode("utf-8"))
3:         overwrite_values = overwrite_values if overwrite_values else {}
4:         for tuning_param in AUTOTUNING_ARGS:
5:             # TODO: This is for autotuning specifically, may cause surprises for someone with a weird setup
6:             if tuning_param in config:
7:                 overwrite_values[tuning_param] = config[tuning_param]
8:         return overwrite_values
9:
10: set_up_autotuning('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', {'train_iters': 32})

Question: What is the value of ' overwrite_values ' in line '7' after '1' th iteration when 'set_up_autotuning('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', {'train_iters': 32})' is executed?

Answer: {'train_iters': 32, 'train_batch_size': 4}