[API Clean]Clean __all__ to avoid exposing usless API (#48713)

* [API Clean]Clean __all__ to avoid exposing usless API

* fix import

* fix typo

* remove tracedLayer unittest

python/paddle/fluid/tests/unittests/test_directory_migration.py

@@ -48,7 +48,6 @@ def test_new_directory(self):
             'paddle.distributed.ParallelEnv',
             'paddle.DataParallel',
             'paddle.jit',
-            'paddle.jit.TracedLayer',
             'paddle.jit.to_static',
             'paddle.jit.ProgramTranslator',
             'paddle.jit.TranslatedLayer',

python/paddle/fluid/tests/unittests/test_imperative_mnist.py

@@ -21,7 +21,7 @@
 import paddle
 import paddle.fluid as fluid
 from paddle.fluid import core
-from paddle.fluid.framework import _in_legacy_dygraph, _test_eager_guard
+from paddle.fluid.framework import _test_eager_guard
 from paddle.fluid.optimizer import SGDOptimizer
 from paddle.nn import Linear
 
@@ -153,19 +153,7 @@ def func_test_mnist_float32(self):
                     dy_x_data = img.numpy()
                     label = data[1]
                     label.stop_gradient = True
-
-                    if batch_id % 10 == 0 and _in_legacy_dygraph():
-                        cost, traced_layer = paddle.jit.TracedLayer.trace(
-                            mnist, inputs=img
-                        )
-                        if program is not None:
-                            self.assertTrue(program, traced_layer.program)
-                        program = traced_layer.program
-                        traced_layer.save_inference_model(
-                            './infer_imperative_mnist'
-                        )
-                    else:
-                        cost = mnist(img)
+                    cost = mnist(img)
 
                     if traced_layer is not None:
                         cost_static = traced_layer([img])

python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py

@@ -16,17 +16,16 @@
 
 import numpy as np
 from test_imperative_base import new_program_scope
-from utils import DyGraphProgramDescTracerTestHelper, is_equal_program
+from utils import DyGraphProgramDescTracerTestHelper
 
 import paddle
 import paddle.fluid as fluid
 import paddle.fluid.core as core
 import paddle.fluid.framework as framework
 from paddle.fluid.dygraph.base import to_variable
 from paddle.fluid.dygraph.nn import Embedding
-from paddle.fluid.framework import _in_legacy_dygraph, _test_eager_guard
+from paddle.fluid.framework import _test_eager_guard
 from paddle.fluid.optimizer import SGDOptimizer
-from paddle.jit import TracedLayer
 
 
 class SimpleLSTMRNN(fluid.Layer):
@@ -298,25 +297,8 @@ def ptb_rnn_cpu_float32(self, is_sparse):
                 y = to_variable(y_data)
                 init_hidden = to_variable(init_hidden_data)
                 init_cell = to_variable(init_cell_data)
-                if i % 5 == 0 and _in_legacy_dygraph():
-                    outs, traced_layer = TracedLayer.trace(
-                        ptb_model, [x, y, init_hidden, init_cell]
-                    )
-                    outs_static = traced_layer([x, y, init_hidden, init_cell])
-                    helper.assertEachVar(outs, outs_static)
-
-                    if program is not None:
-                        self.assertTrue(
-                            is_equal_program(traced_layer.program, program)
-                        )
 
-                    program = traced_layer.program
-
-                    traced_layer.save_inference_model(
-                        './infe_imperative_ptb_rnn', feed=list(range(4))
-                    )
-                else:
-                    outs = ptb_model(x, y, init_hidden, init_cell)
+                outs = ptb_model(x, y, init_hidden, init_cell)
 
                 dy_loss, last_hidden, last_cell = outs
 

python/paddle/fluid/tests/unittests/test_imperative_resnet.py

@@ -16,15 +16,14 @@
 
 import numpy as np
 from test_imperative_base import new_program_scope
-from utils import DyGraphProgramDescTracerTestHelper, is_equal_program
+from utils import DyGraphProgramDescTracerTestHelper
 
 import paddle
 import paddle.fluid as fluid
 from paddle.fluid import BatchNorm, core
 from paddle.fluid.dygraph.base import to_variable
-from paddle.fluid.framework import _in_legacy_dygraph, _test_eager_guard
+from paddle.fluid.framework import _test_eager_guard
 from paddle.fluid.layer_helper import LayerHelper
-from paddle.jit import TracedLayer
 
 # NOTE(zhiqiu): run with FLAGS_cudnn_deterministic=1
 
@@ -301,20 +300,7 @@ def func_test_resnet_float32(self):
                 label.stop_gradient = True
 
                 out = None
-                if batch_id % 5 == 0 and _in_legacy_dygraph():
-                    out, traced_layer = TracedLayer.trace(resnet, img)
-                    if program is not None:
-                        self.assertTrue(
-                            is_equal_program(program, traced_layer.program)
-                        )
-
-                    traced_layer.save_inference_model(
-                        './infer_imperative_resnet'
-                    )
-
-                    program = traced_layer.program
-                else:
-                    out = resnet(img)
+                out = resnet(img)
 
                 if traced_layer is not None:
                     resnet.eval()

python/paddle/fluid/tests/unittests/test_imperative_transformer_sorted_gradient.py

@@ -23,12 +23,11 @@
 from paddle.fluid import Embedding, Layer, core
 from paddle.fluid.dygraph import guard, to_variable
 from paddle.fluid.framework import _in_legacy_dygraph, _test_eager_guard
-from paddle.jit import TracedLayer
 from paddle.nn import Linear
 
 np.set_printoptions(suppress=True)
 
-from utils import DyGraphProgramDescTracerTestHelper, is_equal_program
+from utils import DyGraphProgramDescTracerTestHelper
 
 
 # Copy from models
@@ -1171,27 +1170,7 @@ def run_dygraph():
 
             for i in range(batch_num):
                 enc_inputs, dec_inputs, label, weights = create_data()
-                if False:
-                    outs, traced_layer = TracedLayer.trace(
-                        transformer, [enc_inputs, dec_inputs, label, weights]
-                    )
-
-                    ins_static = enc_inputs + dec_inputs + [label, weights]
-                    outs_static = traced_layer(ins_static)
-                    helper.assertEachVar(outs, outs_static)
-                    if program is not None:
-                        self.assertTrue(
-                            is_equal_program(program, traced_layer.program)
-                        )
-
-                    program = traced_layer.program
-                    traced_layer.save_inference_model(
-                        './infer_imperative_transformer',
-                        feed=list(range(len(ins_static))),
-                        fetch=list(range(len(outs_static))),
-                    )
-                else:
-                    outs = transformer(enc_inputs, dec_inputs, label, weights)
+                outs = transformer(enc_inputs, dec_inputs, label, weights)
 
                 dy_sum_cost, dy_avg_cost, dy_predict, dy_token_num = outs
 

python/paddle/fluid/tests/unittests/test_op_function_generator.py

@@ -20,8 +20,6 @@
 import paddle.fluid as fluid
 import paddle.fluid.layers as layers
 from paddle import _legacy_C_ops
-from paddle.fluid.framework import in_dygraph_mode
-from paddle.jit.api import TracedLayer
 
 
 class TestTracedLayer(fluid.dygraph.Layer):
@@ -93,20 +91,6 @@ def test_trace_backward(self):
             np.testing.assert_array_equal(y_grad, loss.gradient() * a)
         fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
 
-    def test_traced_layer(self):
-        if in_dygraph_mode():
-            return
-        with fluid.dygraph.guard():
-            layer = TestTracedLayer("test_traced_layer")
-            a = np.random.uniform(-1, 1, self.shape).astype(self.dtype)
-            x = fluid.dygraph.to_variable(a)
-            res_dygraph, static_layer = TracedLayer.trace(
-                layer, inputs=x
-            )  # dygraph out
-            res_static_graph = static_layer([x])[0]
-
-            np.testing.assert_array_equal(res_dygraph.numpy(), res_static_graph)
-
 
 if __name__ == '__main__':
     unittest.main()

python/paddle/jit/__init__.py

@@ -15,7 +15,6 @@
 
 from .api import save
 from .api import load
-from .api import TracedLayer
 from .api import set_code_level
 from .api import set_verbosity
 from .api import declarative as to_static
@@ -34,5 +33,4 @@
     'set_code_level',
     'set_verbosity',
     'not_to_static',
-    'TracedLayer',
 ]

python/paddle/jit/api.py

@@ -74,9 +74,7 @@
 from paddle.fluid.wrapped_decorator import wrap_decorator
 
 __all__ = [
-    'TracedLayer',
     'declarative',
-    'dygraph_to_static_func',
     'set_code_level',
     'set_verbosity',
     'save',

python/paddle/jit/dy2static/__init__.py

@@ -36,6 +36,6 @@
 from .assert_transformer import AssertTransformer
 from .ast_transformer import DygraphToStaticAst
 from .program_translator import convert_to_static
-from .static_analysis import *  # noqa: F403
+from .static_analysis import AstNodeWrapper, NodeVarType, StaticAnalysisVisitor
 
 __all__ = []

python/paddle/jit/dy2static/assert_transformer.py

@@ -22,7 +22,7 @@
     BaseTransformer,
 )
 
-__all__ = ['AssertTransformer']
+__all__ = []
 
 
 class AssertTransformer(BaseTransformer):

python/paddle/jit/dy2static/ast_transformer.py

@@ -71,7 +71,7 @@
 from . import logging_utils
 from .utils import ast_to_source_code
 
-__all__ = ['DygraphToStaticAst']
+__all__ = []
 
 
 def apply_optimization(transformers):

python/paddle/jit/dy2static/base_transformer.py

@@ -27,6 +27,8 @@
     get_attribute_full_name,
 )
 
+__all__ = []
+
 
 class BaseTransformer(gast.NodeTransformer):
     def visit(self, node):

python/paddle/jit/dy2static/basic_api_transformer.py

@@ -23,6 +23,8 @@
     BaseTransformer,
 )
 
+__all__ = []
+
 
 class BasicApiTransformer(BaseTransformer):
     """

python/paddle/jit/dy2static/break_continue_transformer.py

@@ -27,7 +27,7 @@
     ForNodeVisitor,
 )
 
-__all__ = ['BreakContinueTransformer']
+__all__ = []
 
 BREAK_NAME_PREFIX = '__break'
 CONTINUE_NAME_PREFIX = '__continue'

python/paddle/jit/dy2static/call_transformer.py

@@ -25,6 +25,8 @@
 
 PDB_SET = "pdb.set_trace"
 
+__all__ = []
+
 
 class CallTransformer(BaseTransformer):
     """

python/paddle/jit/dy2static/cast_transformer.py

@@ -22,6 +22,8 @@
     BaseTransformer,
 )
 
+__all__ = []
+
 
 class CastTransformer(BaseTransformer):
     """

python/paddle/jit/dy2static/convert_call_func.py

@@ -40,7 +40,7 @@
 from paddle.jit.dy2static.utils import is_paddle_func, unwrap
 from paddle.fluid.dygraph.layers import Layer
 
-__all__ = ["convert_call"]
+__all__ = []
 
 
 # The api(s) should be considered as plain function and convert

python/paddle/jit/dy2static/convert_operators.py

@@ -15,7 +15,7 @@
 import re
 import paddle
 from paddle.fluid.data_feeder import convert_dtype
-from paddle.jit.dy2static.variable_trans_func import (
+from .variable_trans_func import (
     to_static_variable,
 )
 from paddle.fluid.framework import core, Variable
@@ -43,10 +43,13 @@
 from paddle.jit.dy2static.utils import (
     UndefinedVar,
     Dygraph2StaticException,
+    GetterSetterHelper,
 )
-from paddle.jit.dy2static.utils import GetterSetterHelper
+
 from paddle.fluid.layers.utils import copy_mutable_vars
 
+__all__ = []
+
 
 def convert_attr(x, attr):
     if isinstance(x, Variable) and attr == "size":

python/paddle/jit/dy2static/create_variable_transformer.py

@@ -12,20 +12,23 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from paddle.jit.dy2static.static_analysis import (
+from .static_analysis import (
     AstNodeWrapper,
 )
-from paddle.jit.dy2static.utils import (
+from .utils import (
     FunctionNameLivenessAnalysis,
 )
-from paddle.jit.dy2static.variable_trans_func import (
+from .variable_trans_func import (
     create_undefined_var,
 )
 from .base_transformer import (
     BaseTransformer,
 )
 
 
+__all__ = []
+
+
 class CreateVariableTransformer(BaseTransformer):
     """ """
 

python/paddle/jit/dy2static/decorator_transformer.py

@@ -14,13 +14,13 @@
 # limitations under the License.
 
 from paddle.utils import gast
-from paddle.jit.dy2static.static_analysis import (
+from .static_analysis import (
     AstNodeWrapper,
 )
 from .base_transformer import (
     BaseTransformer,
 )
-from paddle.jit.dy2static.utils import (
+from .utils import (
     RE_PYNAME,
     RE_PYMODULE,
     ast_to_source_code,
@@ -29,6 +29,8 @@
 
 import re
 
+__all__ = []
+
 IGNORE_NAMES = [
     'declarative',
     'to_static',

python/paddle/jit/dy2static/early_return_transformer.py

@@ -13,14 +13,14 @@
 # limitations under the License.
 
 from paddle.utils import gast
-from paddle.jit.dy2static.static_analysis import (
+from .static_analysis import (
     AstNodeWrapper,
 )
 from .base_transformer import (
     BaseTransformer,
 )
 
-__all__ = ['EarlyReturnTransformer']
+__all__ = []
 
 
 class EarlyReturnTransformer(BaseTransformer):