#!/usr/bin/env python3
# -*- coding: utf-8 -*-

# Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
# See https://llvm.org/LICENSE.txt for license information.
# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception

# Script for updating SPIR-V dialect by scraping information from SPIR-V
# HTML and JSON specs from the Internet.
#
# For example, to define the enum attribute for SPIR-V memory model:
#
# ./gen_spirv_dialect.py --base_td_path /path/to/SPIRVBase.td \
#                        --new-enum MemoryModel
#
# The 'operand_kinds' dict of spirv.core.grammar.json contains all supported
# SPIR-V enum classes.

import itertools
import re
import requests
import textwrap
import yaml

SPIRV_HTML_SPEC_URL = 'https://www.khronos.org/registry/spir-v/specs/unified1/SPIRV.html'
SPIRV_JSON_SPEC_URL = 'https://raw.githubusercontent.com/KhronosGroup/SPIRV-Headers/master/include/spirv/unified1/spirv.core.grammar.json'

AUTOGEN_OP_DEF_SEPARATOR = '\n// -----\n\n'
AUTOGEN_ENUM_SECTION_MARKER = 'enum section. Generated from SPIR-V spec; DO NOT MODIFY!'
AUTOGEN_OPCODE_SECTION_MARKER = (
    'opcode section. Generated from SPIR-V spec; DO NOT MODIFY!')


def get_spirv_doc_from_html_spec():
  """Extracts instruction documentation from SPIR-V HTML spec.

  Returns:
    - A dict mapping from instruction opcode to documentation.
  """
  response = requests.get(SPIRV_HTML_SPEC_URL)
  spec = response.content

  from bs4 import BeautifulSoup
  spirv = BeautifulSoup(spec, 'html.parser')

  section_anchor = spirv.find('h3', {'id': '_a_id_instructions_a_instructions'})

  doc = {}

  for section in section_anchor.parent.find_all('div', {'class': 'sect3'}):
    for table in section.find_all('table'):
      inst_html = table.tbody.tr.td.p
      opname = inst_html.a['id']
      # Ignore the first line, which is just the opname.
      doc[opname] = inst_html.text.split('\n', 1)[1].strip()

  return doc


def get_spirv_grammar_from_json_spec():
  """Extracts operand kind and instruction grammar from SPIR-V JSON spec.

  Returns:
    - A list containing all operand kinds' grammar
    - A list containing all instructions' grammar
  """
  response = requests.get(SPIRV_JSON_SPEC_URL)
  spec = response.content

  import json
  spirv = json.loads(spec)

  return spirv['operand_kinds'], spirv['instructions']


def split_list_into_sublists(items):
  """Split the list of items into multiple sublists.

  This is to make sure the string composed from each sublist won't exceed
  80 characters.

  Arguments:
    - items: a list of strings
  """
  chuncks = []
  chunk = []
  chunk_len = 0

  for item in items:
    chunk_len += len(item) + 2
    if chunk_len > 80:
      chuncks.append(chunk)
      chunk = []
      chunk_len = len(item) + 2
    chunk.append(item)

  if len(chunk) != 0:
    chuncks.append(chunk)

  return chuncks


def uniquify_enum_cases(lst):
  """Prunes duplicate enum cases from the list.

  Arguments:
   - lst: List whose elements are to be uniqued. Assumes each element is a
     (symbol, value) pair and elements already sorted according to value.

  Returns:
   - A list with all duplicates removed. The elements are sorted according to
     value and, for each value, uniqued according to symbol.
     original list,
   - A map from deduplicated cases to the uniqued case.
  """
  cases = lst
  uniqued_cases = []
  duplicated_cases = {}

  # First sort according to the value
  cases.sort(key=lambda x: x[1])

  # Then group them according to the value
  for _, groups in itertools.groupby(cases, key=lambda x: x[1]):
    # For each value, sort according to the enumerant symbol.
    sorted_group = sorted(groups, key=lambda x: x[0])
    # Keep the "smallest" case, which is typically the symbol without extension
    # suffix. But we have special cases that we want to fix.
    case = sorted_group[0]
    for i in range(1, len(sorted_group)):
      duplicated_cases[sorted_group[i][0]] = case[0]
    if case[0] == 'HlslSemanticGOOGLE':
      assert len(sorted_group) == 2, 'unexpected new variant for HlslSemantic'
      case = sorted_group[1]
      duplicated_cases[sorted_group[0][0]] = case[0]
    uniqued_cases.append(case)

  return uniqued_cases, duplicated_cases


def toposort(dag, sort_fn):
  """Topologically sorts the given dag.

  Arguments:
    - dag: a dict mapping from a node to its incoming nodes.
    - sort_fn: a function for sorting nodes in the same batch.

  Returns:
    A list containing topologically sorted nodes.
  """

  # Returns the next batch of nodes without incoming edges
  def get_next_batch(dag):
    while True:
      no_prev_nodes = set(node for node, prev in dag.items() if not prev)
      if not no_prev_nodes:
        break
      yield sorted(no_prev_nodes, key=sort_fn)
      dag = {
          node: (prev - no_prev_nodes)
          for node, prev in dag.items()
          if node not in no_prev_nodes
      }
    assert not dag, 'found cyclic dependency'

  sorted_nodes = []
  for batch in get_next_batch(dag):
    sorted_nodes.extend(batch)

  return sorted_nodes


def toposort_capabilities(all_cases, capability_mapping):
  """Returns topologically sorted capability (symbol, value) pairs.

  Arguments:
    - all_cases: all capability cases (containing symbol, value, and implied
      capabilities).
    - capability_mapping: mapping from duplicated capability symbols to the
      canonicalized symbol chosen for SPIRVBase.td.

  Returns:
    A list containing topologically sorted capability (symbol, value) pairs.
  """
  dag = {}
  name_to_value = {}
  for case in all_cases:
    # Get the current capability.
    cur = case['enumerant']
    name_to_value[cur] = case['value']
    # Ignore duplicated symbols.
    if cur in capability_mapping:
      continue

    # Get capabilities implied by the current capability.
    prev = case.get('capabilities', [])
    uniqued_prev = set([capability_mapping.get(c, c) for c in prev])
    dag[cur] = uniqued_prev

  sorted_caps = toposort(dag, lambda x: name_to_value[x])
  # Attach the capability's value as the second component of the pair.
  return [(c, name_to_value[c]) for c in sorted_caps]


def get_capability_mapping(operand_kinds):
  """Returns the capability mapping from duplicated cases to canonicalized ones.

  Arguments:
    - operand_kinds: all operand kinds' grammar spec

  Returns:
    - A map mapping from duplicated capability symbols to the canonicalized
      symbol chosen for SPIRVBase.td.
  """
  # Find the operand kind for capability
  cap_kind = {}
  for kind in operand_kinds:
    if kind['kind'] == 'Capability':
      cap_kind = kind

  kind_cases = [
      (case['enumerant'], case['value']) for case in cap_kind['enumerants']
  ]
  _, capability_mapping = uniquify_enum_cases(kind_cases)

  return capability_mapping


def get_availability_spec(enum_case, capability_mapping, for_op, for_cap):
  """Returns the availability specification string for the given enum case.

  Arguments:
    - enum_case: the enum case to generate availability spec for. It may contain
      'version', 'lastVersion', 'extensions', or 'capabilities'.
    - capability_mapping: mapping from duplicated capability symbols to the
      canonicalized symbol chosen for SPIRVBase.td.
    - for_op: bool value indicating whether this is the availability spec for an
      op itself.
    - for_cap: bool value indicating whether this is the availability spec for
      capabilities themselves.

  Returns:
    - A `let availability = [...];` string if with availability spec or
      empty string if without availability spec
  """
  assert not (for_op and for_cap), 'cannot set both for_op and for_cap'

  DEFAULT_MIN_VERSION = 'MinVersion<SPV_V_1_0>'
  DEFAULT_MAX_VERSION = 'MaxVersion<SPV_V_1_5>'
  DEFAULT_CAP = 'Capability<[]>'
  DEFAULT_EXT = 'Extension<[]>'

  min_version = enum_case.get('version', '')
  if min_version == 'None':
    min_version = ''
  elif min_version:
    min_version = 'MinVersion<SPV_V_{}>'.format(min_version.replace('.', '_'))
  # TODO: delete this once ODS can support dialect-specific content
  # and we can use omission to mean no requirements.
  if for_op and not min_version:
    min_version = DEFAULT_MIN_VERSION

  max_version = enum_case.get('lastVersion', '')
  if max_version:
    max_version = 'MaxVersion<SPV_V_{}>'.format(max_version.replace('.', '_'))
  # TODO: delete this once ODS can support dialect-specific content
  # and we can use omission to mean no requirements.
  if for_op and not max_version:
    max_version = DEFAULT_MAX_VERSION

  exts = enum_case.get('extensions', [])
  if exts:
    exts = 'Extension<[{}]>'.format(', '.join(sorted(set(exts))))
    # We need to strip the minimal version requirement if this symbol is
    # available via an extension, which means *any* SPIR-V version can support
    # it as long as the extension is provided. The grammar's 'version' field
    # under such case should be interpreted as this symbol is introduced as
    # a core symbol since the given version, rather than a minimal version
    # requirement.
    min_version = DEFAULT_MIN_VERSION if for_op else ''
  # TODO: delete this once ODS can support dialect-specific content
  # and we can use omission to mean no requirements.
  if for_op and not exts:
    exts = DEFAULT_EXT

  caps = enum_case.get('capabilities', [])
  implies = ''
  if caps:
    canonicalized_caps = []
    for c in caps:
      if c in capability_mapping:
        canonicalized_caps.append(capability_mapping[c])
      else:
        canonicalized_caps.append(c)
    prefixed_caps = [
        'SPV_C_{}'.format(c) for c in sorted(set(canonicalized_caps))
    ]
    if for_cap:
      # If this is generating the availability for capabilities, we need to
      # put the capability "requirements" in implies field because now
      # the "capabilities" field in the source grammar means so.
      caps = ''
      implies = 'list<I32EnumAttrCase> implies = [{}];'.format(
          ', '.join(prefixed_caps))
    else:
      caps = 'Capability<[{}]>'.format(', '.join(prefixed_caps))
      implies = ''
  # TODO: delete this once ODS can support dialect-specific content
  # and we can use omission to mean no requirements.
  if for_op and not caps:
    caps = DEFAULT_CAP

  avail = ''
  # Compose availability spec if any of the requirements is not empty.
  # For ops, because we have a default in SPV_Op class, omit if the spec
  # is the same.
  if (min_version or max_version or caps or exts) and not (
      for_op and min_version == DEFAULT_MIN_VERSION and
      max_version == DEFAULT_MAX_VERSION and caps == DEFAULT_CAP and
      exts == DEFAULT_EXT):
    joined_spec = ',\n    '.join(
        [e for e in [min_version, max_version, exts, caps] if e])
    avail = '{} availability = [\n    {}\n  ];'.format(
        'let' if for_op else 'list<Availability>', joined_spec)

  return '{}{}{}'.format(implies, '\n  ' if implies and avail else '', avail)


def gen_operand_kind_enum_attr(operand_kind, capability_mapping):
  """Generates the TableGen EnumAttr definition for the given operand kind.

  Returns:
    - The operand kind's name
    - A string containing the TableGen EnumAttr definition
  """
  if 'enumerants' not in operand_kind:
    return '', ''

  # Returns a symbol for the given case in the given kind. This function
  # handles Dim specially to avoid having numbers as the start of symbols,
  # which does not play well with C++ and the MLIR parser.
  def get_case_symbol(kind_name, case_name):
    if kind_name == 'Dim':
      if case_name == '1D' or case_name == '2D' or case_name == '3D':
        return 'Dim{}'.format(case_name)
    return case_name

  kind_name = operand_kind['kind']
  is_bit_enum = operand_kind['category'] == 'BitEnum'
  kind_category = 'Bit' if is_bit_enum else 'I32'
  kind_acronym = ''.join([c for c in kind_name if c >= 'A' and c <= 'Z'])

  name_to_case_dict = {}
  for case in operand_kind['enumerants']:
    name_to_case_dict[case['enumerant']] = case

  if kind_name == 'Capability':
    # Special treatment for capability cases: we need to sort them topologically
    # because a capability can refer to another via the 'implies' field.
    kind_cases = toposort_capabilities(operand_kind['enumerants'],
                                       capability_mapping)
  else:
    kind_cases = [(case['enumerant'], case['value'])
                  for case in operand_kind['enumerants']]
    kind_cases, _ = uniquify_enum_cases(kind_cases)
  max_len = max([len(symbol) for (symbol, _) in kind_cases])

  # Generate the definition for each enum case
  fmt_str = 'def SPV_{acronym}_{case} {colon:>{offset}} '\
            '{category}EnumAttrCase<"{symbol}", {value}>{avail}'
  case_defs = []
  for case in kind_cases:
    avail = get_availability_spec(name_to_case_dict[case[0]],
                                  capability_mapping,
                                  False, kind_name == 'Capability')
    case_def = fmt_str.format(
        category=kind_category,
        acronym=kind_acronym,
        case=case[0],
        symbol=get_case_symbol(kind_name, case[0]),
        value=case[1],
        avail=' {{\n  {}\n}}'.format(avail) if avail else ';',
        colon=':',
        offset=(max_len + 1 - len(case[0])))
    case_defs.append(case_def)
  case_defs = '\n'.join(case_defs)

  # Generate the list of enum case names
  fmt_str = 'SPV_{acronym}_{symbol}';
  case_names = [fmt_str.format(acronym=kind_acronym,symbol=case[0])
                for case in kind_cases]

  # Split them into sublists and concatenate into multiple lines
  case_names = split_list_into_sublists(case_names)
  case_names = ['{:6}'.format('') + ', '.join(sublist)
                for sublist in case_names]
  case_names = ',\n'.join(case_names)

  # Generate the enum attribute definition
  enum_attr = '''def SPV_{name}Attr :
    SPV_{category}EnumAttr<"{name}", "valid SPIR-V {name}", [
{cases}
    ]>;'''.format(
          name=kind_name, category=kind_category, cases=case_names)
  return kind_name, case_defs + '\n\n' + enum_attr


def gen_opcode(instructions):
  """ Generates the TableGen definition to map opname to opcode

  Returns:
    - A string containing the TableGen SPV_OpCode definition
  """

  max_len = max([len(inst['opname']) for inst in instructions])
  def_fmt_str = 'def SPV_OC_{name} {colon:>{offset}} '\
            'I32EnumAttrCase<"{name}", {value}>;'
  opcode_defs = [
      def_fmt_str.format(
          name=inst['opname'],
          value=inst['opcode'],
          colon=':',
          offset=(max_len + 1 - len(inst['opname']))) for inst in instructions
  ]
  opcode_str = '\n'.join(opcode_defs)

  decl_fmt_str = 'SPV_OC_{name}'
  opcode_list = [
      decl_fmt_str.format(name=inst['opname']) for inst in instructions
  ]
  opcode_list = split_list_into_sublists(opcode_list)
  opcode_list = [
      '{:6}'.format('') + ', '.join(sublist) for sublist in opcode_list
  ]
  opcode_list = ',\n'.join(opcode_list)
  enum_attr = 'def SPV_OpcodeAttr :\n'\
              '    SPV_I32EnumAttr<"{name}", "valid SPIR-V instructions", [\n'\
              '{lst}\n'\
              '    ]>;'.format(name='Opcode', lst=opcode_list)
  return opcode_str + '\n\n' + enum_attr

def map_cap_to_opnames(instructions):
  """Maps capabilities to instructions enabled by those capabilities

  Arguments:
    - instructions: a list containing a subset of SPIR-V instructions' grammar
  Returns:
    - A map with keys representing capabilities and values of lists of
    instructions enabled by the corresponding key
  """
  cap_to_inst = {}

  for inst in instructions:
    caps = inst['capabilities'] if 'capabilities' in inst else ['0_core_0']
    for cap in caps:
      if cap not in cap_to_inst:
        cap_to_inst[cap] = []
      cap_to_inst[cap].append(inst['opname'])

  return cap_to_inst

def gen_instr_coverage_report(path, instructions):
  """Dumps to standard output a YAML report of current instruction coverage

  Arguments:
    - path: the path to SPIRBase.td
    - instructions: a list containing all SPIR-V instructions' grammar
  """
  with open(path, 'r') as f:
    content = f.read()

  content = content.split(AUTOGEN_OPCODE_SECTION_MARKER)

  existing_opcodes = [k[11:] for k in re.findall('def SPV_OC_\w+', content[1])]
  existing_instructions = list(
          filter(lambda inst: (inst['opname'] in existing_opcodes),
              instructions))

  instructions_opnames = [inst['opname'] for inst in instructions]

  remaining_opcodes = list(set(instructions_opnames) - set(existing_opcodes))
  remaining_instructions = list(
          filter(lambda inst: (inst['opname'] in remaining_opcodes),
              instructions))

  rem_cap_to_instr = map_cap_to_opnames(remaining_instructions)
  ex_cap_to_instr = map_cap_to_opnames(existing_instructions)

  rem_cap_to_cov = {}

  # Calculate coverage for each capability
  for cap in rem_cap_to_instr:
    if cap not in ex_cap_to_instr:
      rem_cap_to_cov[cap] = 0.0
    else:
      rem_cap_to_cov[cap] = \
              (len(ex_cap_to_instr[cap]) / (len(ex_cap_to_instr[cap]) \
              + len(rem_cap_to_instr[cap])))

  report = {}

  # Merge the 3 maps into one report
  for cap in rem_cap_to_instr:
    report[cap] = {}
    report[cap]['Supported Instructions'] = \
            ex_cap_to_instr[cap] if cap in ex_cap_to_instr else []
    report[cap]['Unsupported Instructions']  = rem_cap_to_instr[cap]
    report[cap]['Coverage'] = '{}%'.format(int(rem_cap_to_cov[cap] * 100))

  print(yaml.dump(report))

def update_td_opcodes(path, instructions, filter_list):
  """Updates SPIRBase.td with new generated opcode cases.

  Arguments:
    - path: the path to SPIRBase.td
    - instructions: a list containing all SPIR-V instructions' grammar
    - filter_list: a list containing new opnames to add
  """

  with open(path, 'r') as f:
    content = f.read()

  content = content.split(AUTOGEN_OPCODE_SECTION_MARKER)
  assert len(content) == 3

  # Extend opcode list with existing list
  existing_opcodes = [k[11:] for k in re.findall('def SPV_OC_\w+', content[1])]
  filter_list.extend(existing_opcodes)
  filter_list = list(set(filter_list))

  # Generate the opcode for all instructions in SPIR-V
  filter_instrs = list(
      filter(lambda inst: (inst['opname'] in filter_list), instructions))
  # Sort instruction based on opcode
  filter_instrs.sort(key=lambda inst: inst['opcode'])
  opcode = gen_opcode(filter_instrs)

  # Substitute the opcode
  content = content[0] + AUTOGEN_OPCODE_SECTION_MARKER + '\n\n' + \
        opcode + '\n\n// End ' + AUTOGEN_OPCODE_SECTION_MARKER \
        + content[2]

  with open(path, 'w') as f:
    f.write(content)


def update_td_enum_attrs(path, operand_kinds, filter_list):
  """Updates SPIRBase.td with new generated enum definitions.

  Arguments:
    - path: the path to SPIRBase.td
    - operand_kinds: a list containing all operand kinds' grammar
    - filter_list: a list containing new enums to add
  """
  with open(path, 'r') as f:
    content = f.read()

  content = content.split(AUTOGEN_ENUM_SECTION_MARKER)
  assert len(content) == 3

  # Extend filter list with existing enum definitions
  existing_kinds = [
      k[8:-4] for k in re.findall('def SPV_\w+Attr', content[1])]
  filter_list.extend(existing_kinds)

  capability_mapping = get_capability_mapping(operand_kinds)

  # Generate definitions for all enums in filter list
  defs = [
      gen_operand_kind_enum_attr(kind, capability_mapping)
      for kind in operand_kinds
      if kind['kind'] in filter_list
  ]
  # Sort alphabetically according to enum name
  defs.sort(key=lambda enum : enum[0])
  # Only keep the definitions from now on
  # Put Capability's definition at the very beginning because capability cases
  # will be referenced later
  defs = [enum[1] for enum in defs if enum[0] == 'Capability'
         ] + [enum[1] for enum in defs if enum[0] != 'Capability']

  # Substitute the old section
  content = content[0] + AUTOGEN_ENUM_SECTION_MARKER + '\n\n' + \
      '\n\n'.join(defs) + "\n\n// End " + AUTOGEN_ENUM_SECTION_MARKER  \
      + content[2];

  with open(path, 'w') as f:
    f.write(content)


def snake_casify(name):
  """Turns the given name to follow snake_case convention."""
  name = re.sub('\W+', '', name).split()
  name = [s.lower() for s in name]
  return '_'.join(name)


def map_spec_operand_to_ods_argument(operand):
  """Maps an operand in SPIR-V JSON spec to an op argument in ODS.

  Arguments:
    - A dict containing the operand's kind, quantifier, and name

  Returns:
    - A string containing both the type and name for the argument
  """
  kind = operand['kind']
  quantifier = operand.get('quantifier', '')

  # These instruction "operands" are for encoding the results; they should
  # not be handled here.
  assert kind != 'IdResultType', 'unexpected to handle "IdResultType" kind'
  assert kind != 'IdResult', 'unexpected to handle "IdResult" kind'

  if kind == 'IdRef':
    if quantifier == '':
      arg_type = 'SPV_Type'
    elif quantifier == '?':
      arg_type = 'Optional<SPV_Type>'
    else:
      arg_type = 'Variadic<SPV_Type>'
  elif kind == 'IdMemorySemantics' or kind == 'IdScope':
    # TODO: Need to further constrain 'IdMemorySemantics'
    # and 'IdScope' given that they should be generated from OpConstant.
    assert quantifier == '', ('unexpected to have optional/variadic memory '
                              'semantics or scope <id>')
    arg_type = 'SPV_' + kind[2:] + 'Attr'
  elif kind == 'LiteralInteger':
    if quantifier == '':
      arg_type = 'I32Attr'
    elif quantifier == '?':
      arg_type = 'OptionalAttr<I32Attr>'
    else:
      arg_type = 'OptionalAttr<I32ArrayAttr>'
  elif kind == 'LiteralString' or \
      kind == 'LiteralContextDependentNumber' or \
      kind == 'LiteralExtInstInteger' or \
      kind == 'LiteralSpecConstantOpInteger' or \
      kind == 'PairLiteralIntegerIdRef' or \
      kind == 'PairIdRefLiteralInteger' or \
      kind == 'PairIdRefIdRef':
    assert False, '"{}" kind unimplemented'.format(kind)
  else:
    # The rest are all enum operands that we represent with op attributes.
    assert quantifier != '*', 'unexpected to have variadic enum attribute'
    arg_type = 'SPV_{}Attr'.format(kind)
    if quantifier == '?':
      arg_type = 'OptionalAttr<{}>'.format(arg_type)

  name = operand.get('name', '')
  name = snake_casify(name) if name else kind.lower()

  return '{}:${}'.format(arg_type, name)


def get_description(text, appendix):
  """Generates the description for the given SPIR-V instruction.

  Arguments:
    - text: Textual description of the operation as string.
    - appendix: Additional contents to attach in description as string,
                includking IR examples, and others.

  Returns:
    - A string that corresponds to the description of the Tablegen op.
  """
  fmt_str = '{text}\n\n    <!-- End of AutoGen section -->\n{appendix}\n  '
  return fmt_str.format(text=text, appendix=appendix)


def get_op_definition(instruction, doc, existing_info, capability_mapping):
  """Generates the TableGen op definition for the given SPIR-V instruction.

  Arguments:
    - instruction: the instruction's SPIR-V JSON grammar
    - doc: the instruction's SPIR-V HTML doc
    - existing_info: a dict containing potential manually specified sections for
      this instruction
    - capability_mapping: mapping from duplicated capability symbols to the
                   canonicalized symbol chosen for SPIRVBase.td

  Returns:
    - A string containing the TableGen op definition
  """
  fmt_str = ('def SPV_{opname}Op : '
             'SPV_{inst_category}<"{opname}"{category_args}[{traits}]> '
             '{{\n  let summary = {summary};\n\n  let description = '
             '[{{\n{description}}}];{availability}\n')
  inst_category = existing_info.get('inst_category', 'Op')
  if inst_category == 'Op':
    fmt_str +='\n  let arguments = (ins{args});\n\n'\
              '  let results = (outs{results});\n'

  fmt_str +='{extras}'\
            '}}\n'

  opname = instruction['opname'][2:]
  category_args = existing_info.get('category_args', '')

  if '\n' in doc:
    summary, text = doc.split('\n', 1)
  else:
    summary = doc
    text = ''
  wrapper = textwrap.TextWrapper(
      width=76, initial_indent='    ', subsequent_indent='    ')

  # Format summary. If the summary can fit in the same line, we print it out
  # as a "-quoted string; otherwise, wrap the lines using "[{...}]".
  summary = summary.strip();
  if len(summary) + len('  let summary = "";') <= 80:
    summary = '"{}"'.format(summary)
  else:
    summary = '[{{\n{}\n  }}]'.format(wrapper.fill(summary))

  # Wrap text
  text = text.split('\n')
  text = [wrapper.fill(line) for line in text if line]
  text = '\n\n'.join(text)

  operands = instruction.get('operands', [])

  # Op availability
  avail = get_availability_spec(instruction, capability_mapping, True, False)
  if avail:
    avail = '\n\n  {0}'.format(avail)

  # Set op's result
  results = ''
  if len(operands) > 0 and operands[0]['kind'] == 'IdResultType':
    results = '\n    SPV_Type:$result\n  '
    operands = operands[1:]
  if 'results' in existing_info:
    results = existing_info['results']

  # Ignore the operand standing for the result <id>
  if len(operands) > 0 and operands[0]['kind'] == 'IdResult':
    operands = operands[1:]

  # Set op' argument
  arguments = existing_info.get('arguments', None)
  if arguments is None:
    arguments = [map_spec_operand_to_ods_argument(o) for o in operands]
    arguments = ',\n    '.join(arguments)
    if arguments:
      # Prepend and append whitespace for formatting
      arguments = '\n    {}\n  '.format(arguments)

  description = existing_info.get('description', None)
  if description is None:
    assembly = '\n    ```\n'\
               '    [TODO]\n'\
               '    ```mlir\n\n'\
               '    #### Example:\n\n'\
               '    ```\n'\
               '    [TODO]\n' \
               '    ```'
    description = get_description(text, assembly)

  return fmt_str.format(
      opname=opname,
      category_args=category_args,
      inst_category=inst_category,
      traits=existing_info.get('traits', ''),
      summary=summary,
      description=description,
      availability=avail,
      args=arguments,
      results=results,
      extras=existing_info.get('extras', ''))


def get_string_between(base, start, end):
  """Extracts a substring with a specified start and end from a string.

  Arguments:
    - base: string to extract from.
    - start: string to use as the start of the substring.
    - end: string to use as the end of the substring.

  Returns:
    - The substring if found
    - The part of the base after end of the substring. Is the base string itself
      if the substring wasnt found.
  """
  split = base.split(start, 1)
  if len(split) == 2:
    rest = split[1].split(end, 1)
    assert len(rest) == 2, \
           'cannot find end "{end}" while extracting substring '\
           'starting with {start}'.format(start=start, end=end)
    return rest[0].rstrip(end), rest[1]
  return '', split[0]


def get_string_between_nested(base, start, end):
  """Extracts a substring with a nested start and end from a string.

  Arguments:
    - base: string to extract from.
    - start: string to use as the start of the substring.
    - end: string to use as the end of the substring.

  Returns:
    - The substring if found
    - The part of the base after end of the substring. Is the base string itself
      if the substring wasn't found.
  """
  split = base.split(start, 1)
  if len(split) == 2:
    # Handle nesting delimiters
    rest = split[1]
    unmatched_start = 1
    index = 0
    while unmatched_start > 0 and index < len(rest):
      if rest[index:].startswith(end):
        unmatched_start -= 1
        if unmatched_start == 0:
          break
        index += len(end)
      elif rest[index:].startswith(start):
        unmatched_start += 1
        index += len(start)
      else:
        index += 1

    assert index < len(rest), \
           'cannot find end "{end}" while extracting substring '\
           'starting with "{start}"'.format(start=start, end=end)
    return rest[:index], rest[index + len(end):]
  return '', split[0]


def extract_td_op_info(op_def):
  """Extracts potentially manually specified sections in op's definition.

  Arguments: - A string containing the op's TableGen definition

  Returns:
    - A dict containing potential manually specified sections
  """
  # Get opname
  opname = [o[8:-2] for o in re.findall('def SPV_\w+Op', op_def)]
  assert len(opname) == 1, 'more than one ops in the same section!'
  opname = opname[0]

  # Get instruction category
  inst_category = [
      o[4:] for o in re.findall('SPV_\w+Op',
                                op_def.split(':', 1)[1])
  ]
  assert len(inst_category) <= 1, 'more than one ops in the same section!'
  inst_category = inst_category[0] if len(inst_category) == 1 else 'Op'

  # Get category_args
  op_tmpl_params, _ = get_string_between_nested(op_def, '<', '>')
  opstringname, rest = get_string_between(op_tmpl_params, '"', '"')
  category_args = rest.split('[', 1)[0]

  # Get traits
  traits, _ = get_string_between_nested(rest, '[', ']')

  # Get description
  description, rest = get_string_between(op_def, 'let description = [{\n',
                                         '}];\n')

  # Get arguments
  args, rest = get_string_between(rest, '  let arguments = (ins', ');\n')

  # Get results
  results, rest = get_string_between(rest, '  let results = (outs', ');\n')

  extras = rest.strip(' }\n')
  if extras:
    extras = '\n  {}\n'.format(extras)

  return {
      # Prefix with 'Op' to make it consistent with SPIR-V spec
      'opname': 'Op{}'.format(opname),
      'inst_category': inst_category,
      'category_args': category_args,
      'traits': traits,
      'description': description,
      'arguments': args,
      'results': results,
      'extras': extras
  }


def update_td_op_definitions(path, instructions, docs, filter_list,
                             inst_category, capability_mapping):
  """Updates SPIRVOps.td with newly generated op definition.

  Arguments:
    - path: path to SPIRVOps.td
    - instructions: SPIR-V JSON grammar for all instructions
    - docs: SPIR-V HTML doc for all instructions
    - filter_list: a list containing new opnames to include
    - capability_mapping: mapping from duplicated capability symbols to the
                   canonicalized symbol chosen for SPIRVBase.td.

  Returns:
    - A string containing all the TableGen op definitions
  """
  with open(path, 'r') as f:
    content = f.read()

  # Split the file into chunks, each containing one op.
  ops = content.split(AUTOGEN_OP_DEF_SEPARATOR)
  header = ops[0]
  footer = ops[-1]
  ops = ops[1:-1]

  # For each existing op, extract the manually-written sections out to retain
  # them when re-generating the ops. Also append the existing ops to filter
  # list.
  name_op_map = {}  # Map from opname to its existing ODS definition
  op_info_dict = {}
  for op in ops:
    info_dict = extract_td_op_info(op)
    opname = info_dict['opname']
    name_op_map[opname] = op
    op_info_dict[opname] = info_dict
    filter_list.append(opname)
  filter_list = sorted(list(set(filter_list)))

  op_defs = []
  for opname in filter_list:
    # Find the grammar spec for this op
    try:
      instruction = next(
          inst for inst in instructions if inst['opname'] == opname)
      op_defs.append(
          get_op_definition(
              instruction, docs[opname],
              op_info_dict.get(opname, {'inst_category': inst_category}),
              capability_mapping))
    except StopIteration:
      # This is an op added by us; use the existing ODS definition.
      op_defs.append(name_op_map[opname])

  # Substitute the old op definitions
  op_defs = [header] + op_defs + [footer]
  content = AUTOGEN_OP_DEF_SEPARATOR.join(op_defs)

  with open(path, 'w') as f:
    f.write(content)


if __name__ == '__main__':
  import argparse

  cli_parser = argparse.ArgumentParser(
      description='Update SPIR-V dialect definitions using SPIR-V spec')

  cli_parser.add_argument(
      '--base-td-path',
      dest='base_td_path',
      type=str,
      default=None,
      help='Path to SPIRVBase.td')
  cli_parser.add_argument(
      '--op-td-path',
      dest='op_td_path',
      type=str,
      default=None,
      help='Path to SPIRVOps.td')

  cli_parser.add_argument(
      '--new-enum',
      dest='new_enum',
      type=str,
      default=None,
      help='SPIR-V enum to be added to SPIRVBase.td')
  cli_parser.add_argument(
      '--new-opcodes',
      dest='new_opcodes',
      type=str,
      default=None,
      nargs='*',
      help='update SPIR-V opcodes in SPIRVBase.td')
  cli_parser.add_argument(
      '--new-inst',
      dest='new_inst',
      type=str,
      default=None,
      nargs='*',
      help='SPIR-V instruction to be added to ops file')
  cli_parser.add_argument(
      '--inst-category',
      dest='inst_category',
      type=str,
      default='Op',
      help='SPIR-V instruction category used for choosing '\
           'the TableGen base class to define this op')
  cli_parser.add_argument('--gen-inst-coverage', dest='gen_inst_coverage', action='store_true')
  cli_parser.set_defaults(gen_inst_coverage=False)

  args = cli_parser.parse_args()

  operand_kinds, instructions = get_spirv_grammar_from_json_spec()

  # Define new enum attr
  if args.new_enum is not None:
    assert args.base_td_path is not None
    filter_list = [args.new_enum] if args.new_enum else []
    update_td_enum_attrs(args.base_td_path, operand_kinds, filter_list)

  # Define new opcode
  if args.new_opcodes is not None:
    assert args.base_td_path is not None
    update_td_opcodes(args.base_td_path, instructions, args.new_opcodes)

  # Define new op
  if args.new_inst is not None:
    assert args.op_td_path is not None
    docs = get_spirv_doc_from_html_spec()
    capability_mapping = get_capability_mapping(operand_kinds)
    update_td_op_definitions(args.op_td_path, instructions, docs, args.new_inst,
                             args.inst_category, capability_mapping)
    print('Done. Note that this script just generates a template; ', end='')
    print('please read the spec and update traits, arguments, and ', end='')
    print('results accordingly.')

  if args.gen_inst_coverage:
    gen_instr_coverage_report(args.base_td_path, instructions)
