def standard_analysis(node, context, is_initial=False):
"""Performs a complete static analysis of the given code.
Args:
node: ast.AST
context: converter.EntityContext
is_initial: bool, whether this is the initial analysis done on the input
source code
Returns:
ast.AST, same as node, with the static analysis annotations added
"""
# TODO(mdan): Clear static analysis here.
# TODO(mdan): Consider not running all analyses every time.
# TODO(mdan): Don't return a node because it's modified by reference.
graphs = cfg.build(node)
node = qual_names.resolve(node)
node = activity.resolve(node, context, None)
node = reaching_definitions.resolve(node, context, graphs, AnnotatedDef)
node = liveness.resolve(node, context, graphs)
node = live_values.resolve(node, context, config.PYTHON_LITERALS)
node = type_info.resolve(node, context)
# This second call allows resolving first-order class attributes.
node = live_values.resolve(node, context, config.PYTHON_LITERALS)
if is_initial:
anno.dup(
node,
{
anno.Static.DEFINITIONS: anno.Static.ORIG_DEFINITIONS,
},
)
return node
def prepare(self, test_fn, namespace, recursive=True):
namespace['ConversionOptions'] = converter.ConversionOptions
future_features = ('print_function', 'division')
node, source = parser.parse_entity(test_fn, future_features=future_features)
namer = naming.Namer(namespace)
program_ctx = converter.ProgramContext(
options=converter.ConversionOptions(recursive=recursive),
autograph_module=None)
entity_info = transformer.EntityInfo(
name=test_fn.__name__,
source_code=source,
source_file='<fragment>',
future_features=future_features,
namespace=namespace)
ctx = transformer.Context(entity_info, namer, program_ctx)
origin_info.resolve_entity(node, source, test_fn)
graphs = cfg.build(node)
node = qual_names.resolve(node)
node = activity.resolve(node, ctx, None)
node = reaching_definitions.resolve(node, ctx, graphs)
anno.dup(
node,
{
anno.Static.DEFINITIONS: anno.Static.ORIG_DEFINITIONS,
},
)
return node, ctx
def standard_analysis(node, context, is_initial=False):
"""Performs a complete static analysis of the given code.
Args:
node: ast.AST
context: converter.EntityContext
is_initial: bool, whether this is the initial analysis done on the input
source code
Returns:
ast.AST, same as node, with the static analysis annotations added
"""
# TODO(mdan): Clear static analysis here.
# TODO(mdan): Consider not running all analyses every time.
# TODO(mdan): Don't return a node because it's modified by reference.
graphs = cfg.build(node)
node = qual_names.resolve(node)
node = activity.resolve(node, context.info, None)
node = reaching_definitions.resolve(node, context.info, graphs, AnnotatedDef)
node = liveness.resolve(node, context.info, graphs)
node = live_values.resolve(node, context.info, config.PYTHON_LITERALS)
node = type_info.resolve(node, context.info)
# This second call allows resolving first-order class attributes.
node = live_values.resolve(node, context.info, config.PYTHON_LITERALS)
if is_initial:
anno.dup(
node,
{
anno.Static.DEFINITIONS: anno.Static.ORIG_DEFINITIONS,
},
)
return node
def transform_ast(self, node, ctx):
# TODO(mdan): Insert list_comprehensions somewhere.
unsupported_features_checker.verify(node)
# Run initial analysis.
graphs = cfg.build(node)
node = qual_names.resolve(node)
node = activity.resolve(node, ctx, None)
node = reaching_definitions.resolve(node, ctx, graphs)
anno.dup(
node,
{
anno.Static.DEFINITIONS: anno.Static.ORIG_DEFINITIONS,
},
)
node = functions.transform(node, ctx)
node = directives.transform(node, ctx)
node = break_statements.transform(node, ctx)
if ctx.user.options.uses(converter.Feature.ASSERT_STATEMENTS):
node = asserts.transform(node, ctx)
# Note: sequencing continue canonicalization before for loop one avoids
# dealing with the extra loop increment operation that the for
# canonicalization creates.
node = continue_statements.transform(node, ctx)
node = return_statements.transform(node, ctx)
if ctx.user.options.uses(converter.Feature.LISTS):
node = lists.transform(node, ctx)
node = slices.transform(node, ctx)
node = call_trees.transform(node, ctx)
node = control_flow.transform(node, ctx)
node = conditional_expressions.transform(node, ctx)
node = logical_expressions.transform(node, ctx)
return node
def transform_ast(self, node, ctx):
node = qual_names.resolve(node)
node = activity.resolve(node, ctx)
graphs = cfg.build(node)
node = reaching_definitions.resolve(node, ctx, graphs)
node = reaching_fndefs.resolve(node, ctx, graphs)
node = type_inference.resolve(node, ctx, graphs, self.resolver)
return node
def transform(node, ctx): graphs = cfg.build(node) node = qual_names.resolve(node) node = activity.resolve(node, ctx, None) node = reaching_definitions.resolve(node, ctx, graphs, AnnotatedDef) node = liveness.resolve(node, ctx, graphs) node = ControlFlowTransformer(ctx).visit(node) return node
def _parse_and_analyze(self, test_fn):
node, source = parser.parse_entity(test_fn, future_features=())
entity_info = transformer.EntityInfo(
source_code=source, source_file=None, future_features=(), namespace={})
node = qual_names.resolve(node)
ctx = transformer.Context(entity_info)
node = activity.resolve(node, ctx)
graphs = cfg.build(node)
node = reaching_definitions.resolve(node, ctx, graphs,
reaching_definitions.Definition)
return node
def _parse_and_analyze(self, test_fn):
node, source = parser.parse_entity(test_fn, future_features=())
entity_info = transformer.EntityInfo(
source_code=source, source_file=None, future_features=(), namespace={})
node = qual_names.resolve(node)
ctx = transformer.Context(entity_info)
node = activity.resolve(node, ctx)
graphs = cfg.build(node)
node = reaching_definitions.resolve(node, ctx, graphs,
reaching_definitions.Definition)
return node
def initial_analysis(self, node, ctx):
graphs = cfg.build(node)
node = qual_names.resolve(node)
node = activity.resolve(node, ctx, None)
node = reaching_definitions.resolve(node, ctx, graphs)
anno.dup(
node,
{
anno.Static.DEFINITIONS: anno.Static.ORIG_DEFINITIONS,
},
)
return node
def convert4():
node, ctx = get_node_and_ctx(f4)
node = qual_names.resolve(node)
cfgs = cfg.build(node)
node = activity.resolve(node, ctx)
node = reaching_definitions.resolve(node, ctx, cfgs)
node = reaching_fndefs.resolve(node, ctx, cfgs)
node = liveness.resolve(node, ctx, cfgs)
print('live into `b = a + 1`:', anno.getanno(node.body[0], anno.Static.LIVE_VARS_IN))
print('live into `return b`:', anno.getanno(node.body[1], anno.Static.LIVE_VARS_IN))
def mlir_gen_internal(node, entity_info):
"""Returns mlir module for unprocessed node `node`."""
namer = naming.Namer({})
graphs = cfg.build(node)
ctx = transformer.Context(entity_info, namer, None)
node = qual_names.resolve(node)
node = activity.resolve(node, ctx)
node = reaching_definitions.resolve(node, ctx, graphs)
node = reaching_fndefs.resolve(node, ctx, graphs)
node = liveness.resolve(node, ctx, graphs)
mlir_generator = MLIRGen(ctx)
mlir_generator.visit(node)
return mlir_generator.prog
def _parse_and_analyze(self, test_fn):
node, source = parser.parse_entity(test_fn)
entity_info = transformer.EntityInfo(
source_code=source,
source_file=None,
namespace={},
arg_values=None,
arg_types=None,
owner_type=None)
node = qual_names.resolve(node)
node = activity.resolve(node, entity_info)
graphs = cfg.build(node)
node = reaching_definitions.resolve(node, entity_info, graphs,
reaching_definitions.Definition)
return node
def transform_ast(self, node, ctx):
node = _apply_py_to_tf_passes(node, ctx)
# TODO(mdan): Enable this.
# node = anf.transform(node, ctx)
graphs = cfg.build(node)
node = qual_names.resolve(node)
node = activity.resolve(node, ctx)
node = reaching_definitions.resolve(node, ctx, graphs)
node = reaching_fndefs.resolve(node, ctx, graphs)
node = type_inference.resolve(node, ctx, graphs,
TFRTypeResolver(self._op_defs))
mlir_generator = TFRGen(ctx, self._op_defs)
mlir_generator.visit(node)
return mlir_generator.code_buffer
def _parse_and_analyze(self, test_fn):
# TODO(mdan): Use a custom FunctionTransformer here.
node, source = parser.parse_entity(test_fn, future_features=())
entity_info = transformer.EntityInfo(name=test_fn.__name__,
source_code=source,
source_file=None,
future_features=(),
namespace={})
node = qual_names.resolve(node)
namer = naming.Namer({})
ctx = transformer.Context(entity_info, namer, None)
node = activity.resolve(node, ctx)
graphs = cfg.build(node)
node = reaching_definitions.resolve(node, ctx, graphs,
reaching_definitions.Definition)
return node
def _parse_and_analyze(self, test_fn, namespace, arg_types=None):
node, source = parser.parse_entity(test_fn)
entity_info = transformer.EntityInfo(source_code=source,
source_file=None,
namespace=namespace,
arg_values=None,
arg_types=arg_types)
node = qual_names.resolve(node)
graphs = cfg.build(node)
ctx = transformer.Context(entity_info)
node = activity.resolve(node, ctx)
node = reaching_definitions.resolve(node, ctx, graphs,
reaching_definitions.Definition)
node = live_values.resolve(node, ctx, {})
node = type_info.resolve(node, ctx)
node = live_values.resolve(node, ctx, {})
return node
def _parse_and_analyze(self,
test_fn,
namespace,
arg_types=None):
node, source = parser.parse_entity(test_fn)
entity_info = transformer.EntityInfo(
source_code=source,
source_file=None,
namespace=namespace,
arg_values=None,
arg_types=arg_types,
owner_type=None)
node = qual_names.resolve(node)
graphs = cfg.build(node)
ctx = transformer.Context(entity_info)
node = activity.resolve(node, ctx)
node = reaching_definitions.resolve(node, ctx, graphs,
reaching_definitions.Definition)
node = live_values.resolve(node, ctx, {})
node = type_info.resolve(node, ctx)
node = live_values.resolve(node, ctx, {})
return node
