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llvm-project/mlir/utils/spirv/gen_spirv_dialect.py

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#!/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)
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