def prepare(self,
test_fn,
namespace,
namer=None,
arg_types=None,
owner_type=None,
recursive=True,
autograph_decorators=()):
node, source = parser.parse_entity(test_fn)
if namer is None:
namer = FakeNamer()
program_ctx = converter.ProgramContext(
recursive=recursive,
autograph_decorators=autograph_decorators,
partial_types=None,
autograph_module=None,
uncompiled_modules=config.DEFAULT_UNCOMPILED_MODULES)
entity_info = transformer.EntityInfo(
source_code=source,
source_file='<fragment>',
namespace=namespace,
arg_values=None,
arg_types=arg_types,
owner_type=owner_type)
ctx = converter.EntityContext(namer, entity_info, program_ctx)
node = converter.standard_analysis(node, ctx, is_initial=True)
return node, ctx
def prepare(self,
test_fn,
namespace,
namer=None,
arg_types=None,
owner_type=None,
recursive=True,
autograph_decorators=()):
node, source = parser.parse_entity(test_fn)
node = node.body[0]
if namer is None:
namer = FakeNamer()
program_ctx = converter.ProgramContext(
recursive=recursive,
autograph_decorators=autograph_decorators,
partial_types=None,
autograph_module=None,
uncompiled_modules=config.DEFAULT_UNCOMPILED_MODULES)
entity_info = transformer.EntityInfo(source_code=source,
source_file='<fragment>',
namespace=namespace,
arg_values=None,
arg_types=arg_types,
owner_type=owner_type)
ctx = converter.EntityContext(namer, entity_info, program_ctx)
node = converter.standard_analysis(node, ctx, is_initial=True)
return node, ctx
def node_to_graph(node, context, rewrite_errors=True):
"""Convert Python code to equivalent TF graph mode code.
Args:
node: AST, the code to convert.
context: converter.EntityContext
rewrite_errors: Boolean, whether or not to rewrite the error traceback.
Returns:
A tuple (node, deps):
* node: A Python ast node, representing the converted code.
* deps: A set of strings, the fully qualified names of entity
dependencies that this node has.
"""
# TODO(mdan): Insert list_comprehensions somewhere.
node = converter.standard_analysis(node, context, is_initial=True)
# Past this point, line numbers are no longer accurate so we ignore the
# source.
# TODO(mdan): Is it feasible to reconstruct intermediate source code?
context.info.source_code = None
node = converter.apply_(node, context, decorators)
node = converter.apply_(node, context, directives)
node = converter.apply_(node, context, break_statements)
node = converter.apply_(node, context, asserts)
# Note: sequencing continue canonicalization before for loop one avoids
# dealing with the extra loop increment operation that the for
# canonicalization creates.
node = converter.apply_(node, context, continue_statements)
context.info.namespace['len'] = len
node = converter.apply_(node, context, return_statements)
node = converter.apply_(node, context, lists)
node = converter.apply_(node, context, slices)
node = converter.apply_(node, context, builtin_functions)
node = converter.apply_(node, context, call_trees)
node = converter.apply_(node, context, control_flow)
node = converter.apply_(node, context, conditional_expressions)
node = converter.apply_(node, context, logical_expressions)
node = converter.apply_(node, context, side_effect_guards)
node = converter.apply_(node, context, name_scopes)
if rewrite_errors:
node = converter.apply_(node, context, error_handlers)
return node
def node_to_graph(node, context, rewrite_errors=True):
"""Convert Python code to equivalent TF graph mode code.
Args:
node: AST, the code to convert.
context: converter.EntityContext
rewrite_errors: Boolean, whether or not to rewrite the error traceback.
Returns:
A tuple (node, deps):
* node: A Python ast node, representing the converted code.
* deps: A set of strings, the fully qualified names of entity
dependencies that this node has.
"""
# TODO(mdan): Insert list_comprehensions somewhere.
node = converter.standard_analysis(node, context, is_initial=True)
# Past this point, line numbers are no longer accurate so we ignore the
# source.
# TODO(mdan): Is it feasible to reconstruct intermediate source code?
context.info.source_code = None
node = converter.apply_(node, context, decorators)
node = converter.apply_(node, context, directives)
node = converter.apply_(node, context, break_statements)
node = converter.apply_(node, context, asserts)
# Note: sequencing continue canonicalization before for loop one avoids
# dealing with the extra loop increment operation that the for
# canonicalization creates.
node = converter.apply_(node, context, continue_statements)
context.info.namespace['len'] = len
node = converter.apply_(node, context, return_statements)
node = converter.apply_(node, context, lists)
node = converter.apply_(node, context, slices)
node = converter.apply_(node, context, builtin_functions)
node = converter.apply_(node, context, call_trees)
node = converter.apply_(node, context, control_flow)
node = converter.apply_(node, context, conditional_expressions)
node = converter.apply_(node, context, logical_expressions)
node = converter.apply_(node, context, side_effect_guards)
node = converter.apply_(node, context, name_scopes)
if rewrite_errors:
node = converter.apply_(node, context, error_handlers)
return node