call_break_graph_decorator( push_n=1 ) # call instance, in, not in may call TensorVariable.get_py

ParamAliasDecorator( { "output_sizes": ["output_size"], "kernel_sizes": ["kern

triton.autotune( configs=configs, key=['N'], do_bench=do_bench,

size_args_decorator_patch

size_args_decorator_patch

size_args_decorator_patch

size_args_decorator_patch

size_args_decorator_patch

size_args_decorator_patch

param_one_alias(["x", "input"])

param_one_alias(["x", "input"])

param_one_alias(["x", "input"])

param_two_alias(["x", "input"], ["return_mask", "return_indices"])

param_two_alias(["x", "input"], ["return_mask", "return_indices"])

param_two_alias(["x", "input"], ["return_mask", "return_indices"])

param_two_alias(["x", "input"], ["y", "other"])

param_two_alias(["x", "input"], ["y", "other"])

paddle.jit.to_static( input_spec=[InputSpec(shape=[-1, 5])], full_graph=True )

param_two_alias(["x", "input"], ["axis", "dim"])

ParamAliasDecorator( { "x": ["input"], "shape": ["size"], "offset": ["storage_offs

param_one_alias(['x', 'input'])

param_one_alias(["label", "target"])

param_two_alias(["logit", "input"], ["label", "target"])

variadic_tensor_decorator('inputs')

variadic_tensor_decorator('input')

param_two_alias(["x", "input"], ["shape", "size"])

param_two_alias(["x", "input"], ["sorted_sequence", "boundaries"])

Dispatcher.register_decorator(exc_type)

param_two_alias(["x", "input"], ["axis", "dim"])

param_one_alias(["x", "input"])

param_one_alias(['x', 'input'])

param_one_alias(['x', 'input'])

param_one_alias(["x", "input"])

param_one_alias(["x", "input"])

param_one_alias(["x", "input"])

param_one_alias(["x", "input"])

param_one_alias(["x", "input"])

param_one_alias(["x", "input"])

param_two_alias(['x', 'input'], ['y', 'other'])

param_two_alias(["x", "input"], ["axis", "dim"])

unittest.skipIf( core.is_compiled_with_xpu() and core.get_xpu_device_version(0) == core.XPUVersion.XPU

Dispatcher.register_decorator(map)

Dispatcher.register_decorator(zip)

param_one_alias(["label", "target"])

param_two_alias(['x', 'input'], ['axis', 'dim'])

param_two_alias(['x', 'input'], ['axis', 'dim'])

param_one_alias(["x", "input"])

param_two_alias(["x", "input"], ["axis", "dim"])

Dispatcher.register_decorator(operator.eq)

Dispatcher.register_decorator(operator.ne)

param_one_alias(['x', 'input'])

param_one_alias(['x', 'input'])

ParamAliasDecorator( {"x": ["input"], "y": ["src"], "axis1": ["dim1"], "axis2": ["dim2"]} )

param_two_alias(["x", "input"], ["axis", "dim"])

Dispatcher.register_decorator(all)

Dispatcher.register_decorator(any)

Dispatcher.register_decorator(dict)

Dispatcher.register_decorator(dict.fromkeys)

Dispatcher.register_decorator(dict)

Dispatcher.register_decorator(operator.ne)

Dispatcher.register_decorator(operator.eq)

Dispatcher.register_decorator(operator.ne)

Dispatcher.register_decorator(max)

Dispatcher.register_decorator(max)

Dispatcher.register_decorator(min)

Dispatcher.register_decorator(min)

Dispatcher.register_decorator(pow)

Dispatcher.register_decorator(reduce)

Dispatcher.register_decorator(reversed)

Dispatcher.register_decorator(operator.eq)

Dispatcher.register_decorator(operator.ne)

Dispatcher.register_decorator(operator.eq)

Dispatcher.register_decorator(operator.ne)

Dispatcher.register_decorator(sum)

Dispatcher.register_decorator(sum)

Dispatcher.register_decorator(bool)

Dispatcher.register_decorator(operator.not_)

Dispatcher.register_decorator(operator.eq)

Dispatcher.register_decorator(operator.ne)

param_two_alias(["x", "input"], ["y", "other"])

param_two_alias(["x", "input"], ["y", "other"])

param_one_alias(["x", "input"])

ParamAliasDecorator( { "x": ["input"], "num_or_indices": ["indices", "sections"], } )

param_one_alias(["x", "input"])

param_one_alias(["x", "input"])

param_two_alias(["x", "input"], ["y", "other"])

param_two_alias(["x", "input"], ["axis", "dim"])

param_two_alias(["x", "input"], ["axes", "dim"])

param_two_alias(["x", "input"], ["axes", "dim"])

param_two_alias(["x", "input"], ["axes", "dim"])

ParamAliasDecorator( {"x": ["input"], "start_axis": ["start_dim"], "stop_axis": ["end_dim"]} )

param_two_alias(['x', 'input'], ['y', 'other'])

paddle.static.register_op( name="fn_with_breakgraph", infer_meta=lambda x, y: paddle.static.MetaTensor

paddle.static.register_op( name="fn_with_constant", infer_meta=lambda x, c: paddle.static.MetaTensor(

paddle.static.register_op( name="fn_with_numpy_operation", infer_meta=lambda x, y: paddle.static.MetaT

ParamAliasDecorator( { "x": ["input"], "output_sizes": ["output_size"], "kernel_si

param_one_alias(["label", "target"])

param_one_alias(["x", "input"])

param_one_alias(["x", "input"])

param_one_alias(["x", "input"])