From fa0f6938ecf7e3d90f93a8c97a9a3eeb728450f2 Mon Sep 17 00:00:00 2001 From: hjyp <53164956+Tomoko-hjf@users.noreply.github.com> Date: Mon, 19 Dec 2022 19:12:43 +0800 Subject: [PATCH] =?UTF-8?q?[Dy2St]=20=E7=A7=BB=E9=99=A4=20declarative=20?= =?UTF-8?q?=E6=8E=A5=E5=8F=A3=20(#49145)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * 移除 declarative 接口 * 修改 CI报错，清理注释 --- python/paddle/fluid/data_feeder.py | 2 +- python/paddle/fluid/dygraph/base.py | 4 +- .../dygraph_to_static/bert_dygraph_model.py | 4 +- .../seq2seq_dygraph_model.py | 8 ++-- .../dygraph_to_static/simnet_dygraph_model.py | 4 +- .../dygraph_to_static/test_assert.py | 4 +- .../dygraph_to_static/test_break_continue.py | 6 +-- .../dygraph_to_static/test_cache_program.py | 6 +-- .../unittests/dygraph_to_static/test_cast.py | 12 +++--- .../dygraph_to_static/test_cycle_gan.py | 8 ++-- .../dygraph_to_static/test_declarative.py | 37 +++++++++---------- .../dygraph_to_static/test_fetch_feed.py | 6 +-- .../dygraph_to_static/test_ifelse.py | 7 ++-- .../unittests/dygraph_to_static/test_lac.py | 4 +- .../dygraph_to_static/test_lambda.py | 3 +- .../unittests/dygraph_to_static/test_len.py | 3 +- .../unittests/dygraph_to_static/test_list.py | 9 +++-- .../unittests/dygraph_to_static/test_loop.py | 5 +-- .../dygraph_to_static/test_mobile_net.py | 6 +-- .../dygraph_to_static/test_origin_info.py | 8 ++-- .../dygraph_to_static/test_partial_program.py | 8 ++-- .../test_program_translator.py | 6 +-- .../dygraph_to_static/test_ptb_lm.py | 4 +- .../test_reinforcement_learning.py | 4 +- .../test_save_inference_model.py | 4 +- .../dygraph_to_static/test_se_resnet.py | 4 +- .../dygraph_to_static/test_sentiment.py | 10 ++--- .../dygraph_to_static/test_tensor_shape.py | 5 ++- .../unittests/dygraph_to_static/test_tsm.py | 4 +- .../dygraph_to_static/test_typehint.py | 4 +- .../dygraph_to_static/test_word2vec.py | 4 +- .../unittests/dygraph_to_static/yolov3.py | 4 +- .../tests/unittests/test_jit_save_load.py | 28 +++++++------- python/paddle/jit/__init__.py | 2 +- python/paddle/jit/api.py | 16 ++++---- .../paddle/jit/dy2static/convert_call_func.py | 4 +- .../paddle/jit/dy2static/partial_program.py | 8 ++-- 37 files changed, 131 insertions(+), 134 deletions(-) diff --git a/python/paddle/fluid/data_feeder.py b/python/paddle/fluid/data_feeder.py index 03fb59c2594..fecb1818f47 100644 --- a/python/paddle/fluid/data_feeder.py +++ b/python/paddle/fluid/data_feeder.py @@ -116,7 +116,7 @@ def check_type(input, input_name, expected_type, op_name, extra_message=''): return # NOTE: `in_declarative_mode` is used to determined whether this op is called under - # @declarative in transformation from dygrah to static layer. We add VarBase in + # @to_static in transformation from dygrah to static layer. We add VarBase in # expected_type to skip checking because varBase may be created and used in unusual way. from .dygraph.base import in_declarative_mode diff --git a/python/paddle/fluid/dygraph/base.py b/python/paddle/fluid/dygraph/base.py index 593ce558f21..fa0c12e1608 100644 --- a/python/paddle/fluid/dygraph/base.py +++ b/python/paddle/fluid/dygraph/base.py @@ -44,13 +44,13 @@ __all__ = [ 'to_variable', ] -# Flag that indicates whether running code under `@declarative` +# Flag that indicates whether running code under `@to_static` _in_declarative_mode_ = False def in_declarative_mode(): """ - Return a bool value that indicates whether running code under `@declarative` + Return a bool value that indicates whether running code under `@to_static` """ return _in_declarative_mode_ diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/bert_dygraph_model.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/bert_dygraph_model.py index 8e5ae7d537f..1ea69dfbb15 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/bert_dygraph_model.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/bert_dygraph_model.py @@ -17,7 +17,7 @@ from transformer_dygraph_model import MultiHeadAttention, PrePostProcessLayer import paddle import paddle.fluid as fluid from paddle.fluid.dygraph import Layer -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.nn import Linear @@ -373,7 +373,7 @@ class PretrainModelLayer(Layer): bias_attr="next_sent_fc.b_0", ) - @declarative + @to_static def forward( self, src_ids, diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/seq2seq_dygraph_model.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/seq2seq_dygraph_model.py index afc3ebf72d0..99d90a7f1ea 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/seq2seq_dygraph_model.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/seq2seq_dygraph_model.py @@ -21,7 +21,7 @@ import paddle.fluid as fluid from paddle.fluid import ParamAttr, layers from paddle.fluid.dygraph import Layer from paddle.fluid.dygraph.base import to_variable -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.nn import Embedding INF = 1.0 * 1e5 @@ -207,7 +207,7 @@ class BaseModel(fluid.dygraph.Layer): topk_coordinates = paddle.stack([batch_pos, indices], axis=2) return paddle.gather_nd(x, topk_coordinates) - @declarative + @to_static def forward(self, inputs): src, tar, label, src_sequence_length, tar_sequence_length = inputs if src.shape[0] < self.batch_size: @@ -312,7 +312,7 @@ class BaseModel(fluid.dygraph.Layer): return loss - @declarative + @to_static def beam_search(self, inputs): src, tar, label, src_sequence_length, tar_sequence_length = inputs if src.shape[0] < self.batch_size: @@ -724,7 +724,7 @@ class AttentionModel(fluid.dygraph.Layer): return array - @declarative + @to_static def forward(self, inputs): src, tar, label, src_sequence_length, tar_sequence_length = inputs if src.shape[0] < self.batch_size: diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/simnet_dygraph_model.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/simnet_dygraph_model.py index b6baf7ddf29..c76b4dba9cb 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/simnet_dygraph_model.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/simnet_dygraph_model.py @@ -18,7 +18,7 @@ import paddle import paddle.fluid as fluid import paddle.fluid.param_attr as attr from paddle.fluid.dygraph import Layer -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.static import Variable @@ -495,7 +495,7 @@ class BOW(Layer): self.bow_layer_po = FCLayer(self.bow_dim, None, "fc").ops() self.softmax_layer = FCLayer(2, "softmax", "cos_sim").ops() - @declarative + @to_static def forward(self, left, right): """ Forward network diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_assert.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_assert.py index e6f821cdb45..0bfd19e7326 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_assert.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_assert.py @@ -19,7 +19,7 @@ import numpy import paddle import paddle.fluid as fluid from paddle.jit import ProgramTranslator -from paddle.jit.api import declarative +from paddle.jit.api import to_static @paddle.jit.to_static @@ -28,7 +28,7 @@ def dyfunc_assert_variable(x): assert x_v -@declarative +@to_static def dyfunc_assert_non_variable(x=True): assert x diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_break_continue.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_break_continue.py index 7ae9248cc38..209f6acbcd1 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_break_continue.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_break_continue.py @@ -18,7 +18,7 @@ import numpy as np import paddle import paddle.fluid as fluid -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.jit.dy2static.program_translator import ProgramTranslator from paddle.jit.dy2static.utils import Dygraph2StaticException @@ -36,7 +36,7 @@ class TestDy2staticException(unittest.TestCase): if self.dyfunc: with self.assertRaisesRegex(Dygraph2StaticException, self.error): ProgramTranslator().enable(True) - self.assertTrue(declarative(self.dyfunc)(self.x)) + self.assertTrue(to_static(self.dyfunc)(self.x)) paddle.fluid.dygraph.base._in_declarative_mode_ = False ProgramTranslator().enable(False) @@ -223,7 +223,7 @@ class TestContinueInFor(unittest.TestCase): def run_static_mode(self): with fluid.dygraph.guard(): - res = declarative(self.dygraph_func)(self.input) + res = to_static(self.dygraph_func)(self.input) return res.numpy() def test_transformed_static_result(self): diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_cache_program.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_cache_program.py index 968dbcb4c15..d4b7c603a1f 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_cache_program.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_cache_program.py @@ -21,7 +21,7 @@ from test_fetch_feed import Linear, Pool2D import paddle import paddle.fluid as fluid from paddle.jit import ProgramTranslator -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.jit.dy2static import convert_to_static @@ -138,7 +138,7 @@ class TestConvertWithCache(unittest.TestCase): self.assertTrue(id(static_func), id(cached_func)) -@declarative +@to_static def sum_even_until_limit(max_len, limit): ret_sum = fluid.dygraph.to_variable(np.zeros((1)).astype('int32')) for i in range(max_len): @@ -166,7 +166,7 @@ class TestToOutputWithCache(unittest.TestCase): ret = sum_even_until_limit(80, 10) self.assertEqual(ret.numpy(), 30) - ret = declarative(sum_under_while)(100) + ret = to_static(sum_under_while)(100) self.assertEqual(ret.numpy(), 5050) diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_cast.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_cast.py index cb768544491..4a848c13658 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_cast.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_cast.py @@ -17,40 +17,40 @@ import unittest import numpy as np import paddle.fluid as fluid -from paddle.jit.api import declarative +from paddle.jit.api import to_static SEED = 2020 np.random.seed(SEED) -@declarative +@to_static def test_bool_cast(x): x = fluid.dygraph.to_variable(x) x = bool(x) return x -@declarative +@to_static def test_int_cast(x): x = fluid.dygraph.to_variable(x) x = int(x) return x -@declarative +@to_static def test_float_cast(x): x = fluid.dygraph.to_variable(x) x = float(x) return x -@declarative +@to_static def test_not_var_cast(x): x = int(x) return x -@declarative +@to_static def test_mix_cast(x): x = fluid.dygraph.to_variable(x) x = int(x) diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_cycle_gan.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_cycle_gan.py index f02da2f513c..988a994a72d 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_cycle_gan.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_cycle_gan.py @@ -39,7 +39,7 @@ os.environ["CUDA_VISIBLE_DEVICES"] = "1" import paddle from paddle.fluid.dygraph import to_variable from paddle.jit import ProgramTranslator -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.nn import BatchNorm # Note: Set True to eliminate randomness. @@ -82,7 +82,7 @@ class Cycle_Gan(fluid.dygraph.Layer): input_channel ) - @declarative + @to_static def forward(self, input_A, input_B): """ Generator of GAN model. @@ -133,7 +133,7 @@ class Cycle_Gan(fluid.dygraph.Layer): g_loss, ) - @declarative + @to_static def discriminatorA(self, input_A, input_B): """ Discriminator A of GAN model. @@ -143,7 +143,7 @@ class Cycle_Gan(fluid.dygraph.Layer): return rec_B, fake_pool_rec_B - @declarative + @to_static def discriminatorB(self, input_A, input_B): """ Discriminator B of GAN model. diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_declarative.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_declarative.py index 4ac7ca9e3c9..572a899d611 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_declarative.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_declarative.py @@ -23,7 +23,7 @@ import paddle import paddle.fluid as fluid from paddle.fluid.dygraph import Layer, to_variable from paddle.jit import ProgramTranslator -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.jit.dy2static.program_translator import ( ConcreteProgram, StaticFunction, @@ -38,13 +38,12 @@ class SimpleNet(Layer): super().__init__() self.linear = paddle.nn.Linear(10, 3) - @declarative(input_spec=[InputSpec(shape=[None, 10], dtype='float32')]) + @to_static(input_spec=[InputSpec(shape=[None, 10], dtype='float32')]) def forward(self, x, a=1, b=2): y = self.inner_function(x) return y - # `declarative` is not essential, add it to test for robustness. - @declarative + @to_static def inner_function(self, x): y = self.linear(x) return y @@ -53,14 +52,14 @@ class SimpleNet(Layer): z = x + y return z - @declarative(input_spec=[[InputSpec([None, 10]), InputSpec([None, 10])]]) + @to_static(input_spec=[[InputSpec([None, 10]), InputSpec([None, 10])]]) def func_with_list(self, l, int_val=1): x, y = l z = x + y z = z + int_val return z - @declarative( + @to_static( input_spec=[{'x': InputSpec([None, 10]), 'y': InputSpec([None, 10])}] ) def func_with_dict(self, d): @@ -70,7 +69,7 @@ class SimpleNet(Layer): return z - @declarative( + @to_static( input_spec=[ [ InputSpec([None]), @@ -135,8 +134,8 @@ class TestInputSpec(unittest.TestCase): # 3. we can decorate any method x_2 = to_variable(np.ones([4, 20]).astype('float32')) - # uses `declarative(func)` instead of `@declarative` - net.add_func = declarative(net.add_func) + # uses `to_static(func)` instead of `@to_static` + net.add_func = to_static(net.add_func) out = net.add_func(x_2, np.ones([20]).astype('float32')) self.assertTrue(len(net.add_func.program_cache) == 1) @@ -164,7 +163,7 @@ class TestInputSpec(unittest.TestCase): # 2. requires len(input_spec) <= len(args) with self.assertRaises(ValueError): - net.add_func = declarative( + net.add_func = to_static( net.add_func, input_spec=[ InputSpec([-1, 10]), @@ -182,7 +181,7 @@ class TestInputSpec(unittest.TestCase): net = SimpleNet() # We can get concrete_program by specificing InputSpec information. Faking input is no need. - net.add_func = declarative( + net.add_func = to_static( net.add_func, input_spec=[InputSpec([-1, 10]), InputSpec([-1, 10], name='y')], ) @@ -191,14 +190,14 @@ class TestInputSpec(unittest.TestCase): self.assertTrue(cp1.inputs[-1].name == 'y') # generate another program - net.add_func = declarative( + net.add_func = to_static( net.add_func, input_spec=[InputSpec([10]), InputSpec([10], name='label')], ) cp2 = net.add_func.concrete_program self.assertTrue(cp2.inputs[-1].shape == (10,)) self.assertTrue(cp2.inputs[-1].name == 'label') - # Note(Aurelius84): New instance will be returned if we use `declarative(foo)` every time. + # Note(Aurelius84): New instance will be returned if we use `to_static(foo)` every time. # So number of cache program is 1. self.assertTrue(len(net.add_func.program_cache) == 1) self.assertTrue(cp1 != cp2) @@ -219,7 +218,7 @@ class TestDifferentInputSpecCacheProgram(unittest.TestCase): y_data = np.ones([10]).astype('float32') * 2 z_data = np.ones([10]).astype('float32') * 2.2 - foo = declarative(foo_func) + foo = to_static(foo_func) # [16, 10] + [10] (varbase) out_1 = foo(to_variable(x_data), to_variable(y_data)) @@ -260,7 +259,7 @@ class TestDifferentInputSpecCacheProgram(unittest.TestCase): def test_get_concrete_program(self): - foo = declarative(foo_func) + foo = to_static(foo_func) # 1. specific InputSpec for `x`/`y` concrete_program_1 = foo.get_concrete_program( @@ -349,7 +348,7 @@ class TestInputDefaultName(unittest.TestCase): class TestDeclarativeAPI(unittest.TestCase): def test_error(self): - func = declarative(dyfunc_to_variable) + func = to_static(dyfunc_to_variable) paddle.enable_static() @@ -373,20 +372,20 @@ class TestDecorateModelDirectly(unittest.TestCase): def test_fake_input(self): net = SimpleNet() - net = declarative(net) + net = to_static(net) y = net(self.x) self.assertTrue(len(net.forward.program_cache) == 1) def test_input_spec(self): net = SimpleNet() - net = declarative(net, input_spec=[InputSpec([None, 8, 10])]) + net = to_static(net, input_spec=[InputSpec([None, 8, 10])]) self.assertTrue(len(net.forward.inputs) == 1) self.assertTrue(len(net.forward.program_cache) == 1) input_shape = net.forward.inputs[0].shape self.assertListEqual(list(input_shape), [-1, 8, 10]) # redecorate - net = declarative(net, input_spec=[InputSpec([None, 16, 10])]) + net = to_static(net, input_spec=[InputSpec([None, 16, 10])]) input_shape = net.forward.inputs[0].shape self.assertListEqual(list(input_shape), [-1, 16, 10]) diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_fetch_feed.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_fetch_feed.py index 74dd84720f5..6cd2c8bd174 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_fetch_feed.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_fetch_feed.py @@ -19,7 +19,7 @@ import numpy as np import paddle import paddle.fluid as fluid from paddle.jit import ProgramTranslator -from paddle.jit.api import declarative +from paddle.jit.api import to_static SEED = 2020 @@ -29,7 +29,7 @@ class Pool2D(fluid.dygraph.Layer): super().__init__() self.pool2d = paddle.nn.AvgPool2D(kernel_size=2, stride=1) - @declarative + @to_static def forward(self, x): # Add func `get_result` for testing arg_name_to_idx in ast transformation. def get_result(x): @@ -54,7 +54,7 @@ class Linear(fluid.dygraph.Layer): ) self.act = paddle.nn.ReLU() - @declarative + @to_static def forward(self, x): pre = self.fc(x) pre = self.act(pre) diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_ifelse.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_ifelse.py index 39f44ff191b..d06ba1b2ec2 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_ifelse.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_ifelse.py @@ -44,7 +44,6 @@ from ifelse_simple_func import ( import paddle import paddle.fluid.core as core import paddle.nn.functional as F -from paddle.jit.api import declarative from paddle.jit.dy2static.program_translator import ProgramTranslator from paddle.jit.dy2static.utils import Dygraph2StaticException @@ -66,7 +65,7 @@ class TestDy2staticException(unittest.TestCase): if self.dyfunc: with self.assertRaisesRegex(Dygraph2StaticException, self.error): ProgramTranslator().enable(True) - self.assertTrue(declarative(self.dyfunc)(self.x)) + self.assertTrue(paddle.jit.to_static(self.dyfunc)(self.x)) paddle.fluid.dygraph.base._in_declarative_mode_ = False ProgramTranslator().enable(False) @@ -89,7 +88,7 @@ class TestDygraphIfElse(unittest.TestCase): with fluid.dygraph.guard(place): x_v = fluid.dygraph.to_variable(self.x) if to_static: - ret = declarative(self.dyfunc)(x_v) + ret = paddle.jit.to_static(self.dyfunc)(x_v) else: ret = self.dyfunc(x_v) return ret.numpy() @@ -293,7 +292,7 @@ class TestAst2FuncWithExternalFunc(TestDygraphIfElse): class NetWithExternalFunc(fluid.dygraph.Layer): - @declarative + @paddle.jit.to_static def forward(self, x, label=None): if paddle.mean(x) < 0: x_v = x - 1 diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_lac.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_lac.py index 80e1a12e5c3..867fe080909 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_lac.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_lac.py @@ -28,7 +28,7 @@ from paddle import _legacy_C_ops from paddle.fluid.dygraph import to_variable from paddle.fluid.framework import _non_static_mode from paddle.jit import ProgramTranslator -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.jit.translated_layer import INFER_MODEL_SUFFIX, INFER_PARAMS_SUFFIX SEED = 2020 @@ -440,7 +440,7 @@ class LexNet(fluid.dygraph.Layer): # share weight self.crf_decoding.weight = self.linear_chain_crf.weight - @declarative(input_spec=input_specs) + @to_static(input_spec=input_specs) def forward(self, word, target, length=None): """ Configure the network diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_lambda.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_lambda.py index 8466a167947..61ef6bb7a16 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_lambda.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_lambda.py @@ -19,7 +19,6 @@ import numpy as np import paddle import paddle.fluid as fluid import paddle.nn.functional as F -from paddle.jit.api import declarative def call_lambda_as_func(x): @@ -108,7 +107,7 @@ class TestLambda(unittest.TestCase): with fluid.dygraph.guard(self.place): x_v = fluid.dygraph.to_variable(self.x) if to_static: - ret = declarative(func)(x_v) + ret = paddle.jit.to_static(func)(x_v) else: ret = func(x_v) return ret.numpy() diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_len.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_len.py index 4802f20f673..de3508afcbe 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_len.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_len.py @@ -18,7 +18,6 @@ import numpy as np import paddle import paddle.fluid as fluid -from paddle.jit.api import declarative from paddle.jit.dy2static import Call SEED = 2020 @@ -58,7 +57,7 @@ class TestLen(unittest.TestCase): def _run(self, to_static): with fluid.dygraph.guard(self.place): if to_static: - out = declarative(self.func)(self.x_data) + out = paddle.jit.to_static(self.func)(self.x_data) else: out = self.func(self.x_data) diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_list.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_list.py index 279d8c9f30e..3dc052cb58d 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_list.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_list.py @@ -20,7 +20,6 @@ import numpy as np import paddle import paddle.fluid as fluid from paddle.fluid.layers.utils import map_structure -from paddle.jit.api import declarative SEED = 2020 np.random.seed(SEED) @@ -247,7 +246,7 @@ class TestListWithoutControlFlow(unittest.TestCase): with fluid.dygraph.guard(): if to_static: - res = declarative(self.dygraph_func)(self.input) + res = paddle.jit.to_static(self.dygraph_func)(self.input) else: res = self.dygraph_func(self.input) return self.varbase_to_numpy(res) @@ -290,8 +289,10 @@ class TestListInWhileLoop(TestListWithoutControlFlow): with fluid.dygraph.guard(): if to_static: - print(declarative(self.dygraph_func).code) - res = declarative(self.dygraph_func)(self.input, self.iter_num) + print(paddle.jit.to_static(self.dygraph_func).code) + res = paddle.jit.to_static(self.dygraph_func)( + self.input, self.iter_num + ) else: res = self.dygraph_func(self.input, self.iter_num) return self.varbase_to_numpy(res) diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_loop.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_loop.py index 454f66b823e..fabfa8edc3c 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_loop.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_loop.py @@ -20,7 +20,6 @@ import numpy as np import paddle import paddle.fluid as fluid import paddle.nn.functional as F -from paddle.jit.api import declarative from paddle.jit.dy2static.loop_transformer import NameVisitor from paddle.utils import gast @@ -324,7 +323,7 @@ class TestTransformWhileLoop(unittest.TestCase): # Set the input of dyfunc to VarBase tensor_x = fluid.dygraph.to_variable(self.x, zero_copy=False) if to_static: - ret = declarative(self.dyfunc)(tensor_x) + ret = paddle.jit.to_static(self.dyfunc)(tensor_x) else: ret = self.dyfunc(tensor_x) if hasattr(ret, "numpy"): @@ -401,7 +400,7 @@ class TestTransformForLoop(unittest.TestCase): def _run(self, to_static): with fluid.dygraph.guard(self.place): if to_static: - ret = declarative(self.dyfunc)(self.len) + ret = paddle.jit.to_static(self.dyfunc)(self.len) else: ret = self.dyfunc(self.len) return ret.numpy() diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_mobile_net.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_mobile_net.py index 2995757660e..d6248dc922f 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_mobile_net.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_mobile_net.py @@ -25,7 +25,7 @@ import paddle.fluid as fluid from paddle.fluid.initializer import MSRA from paddle.fluid.param_attr import ParamAttr from paddle.jit import ProgramTranslator -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.jit.translated_layer import INFER_MODEL_SUFFIX, INFER_PARAMS_SUFFIX from paddle.nn import BatchNorm, Linear @@ -266,7 +266,7 @@ class MobileNetV1(fluid.dygraph.Layer): bias_attr=ParamAttr(name="fc7_offset"), ) - @declarative + @to_static def forward(self, inputs): y = self.conv1(inputs) for dws in self.dwsl: @@ -432,7 +432,7 @@ class MobileNetV2(fluid.dygraph.Layer): bias_attr=ParamAttr(name="fc10_offset"), ) - @declarative + @to_static def forward(self, inputs): y = self._conv1(inputs, if_act=True) for inv in self._invl: diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_origin_info.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_origin_info.py index 540ad3c13bb..90436f6d72b 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_origin_info.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_origin_info.py @@ -15,7 +15,7 @@ import sys import unittest -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.jit.dy2static import DygraphToStaticAst from paddle.jit.dy2static.origin_info import ( ORIGI_INFO, @@ -43,13 +43,13 @@ def nested_func(x): return result -@declarative +@to_static def decorated_func(x): return x -@declarative -@declarative +@to_static +@to_static def decorated_func2(x): return x diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_partial_program.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_partial_program.py index a1a934c3060..cd172d8c97c 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_partial_program.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_partial_program.py @@ -21,7 +21,7 @@ import paddle import paddle.fluid as fluid from paddle.fluid.layers.utils import flatten from paddle.jit import ProgramTranslator -from paddle.jit.api import declarative +from paddle.jit.api import to_static SEED = 2020 @@ -78,7 +78,7 @@ class TestWithNestedInput(unittest.TestCase): self.fake_input() if to_static: - out = declarative(nested_input)(self.x, self.y) + out = paddle.jit.to_static(nested_input)(self.x, self.y) else: out = nested_input(self.x, self.y) @@ -102,7 +102,7 @@ class TestWithNestedOutput(unittest.TestCase): self.y = fake_data([10, 16]) if to_static: - out = declarative(nested_output)(self.x, self.y) + out = paddle.jit.to_static(nested_output)(self.x, self.y) else: out = nested_output(self.x, self.y) @@ -185,7 +185,7 @@ class GPT2LMHeadModel(fluid.dygraph.Layer): np.random.rand(2, 3).astype('float32') ) - @declarative + @to_static def forward(self, x): x = paddle.reshape(x, shape=[-1, 6]) x1, x2, x3 = paddle.split(x=x, axis=1, num_or_sections=3) diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_program_translator.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_program_translator.py index e6dc0e2f30b..11ca4e4343b 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_program_translator.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_program_translator.py @@ -28,7 +28,7 @@ import paddle import paddle.fluid as fluid import paddle.jit.dy2static as _jst from paddle.jit import ProgramTranslator -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.jit.dy2static.utils import func_to_source_code from paddle.utils import gast @@ -47,7 +47,7 @@ def simple_func(x, weight_numpy): return z -@declarative +@to_static def decorated_simple_func(x, weight_numpy): x = fluid.dygraph.to_variable(x) w = fluid.dygraph.to_variable(weight_numpy) @@ -206,7 +206,7 @@ class StaticCode2: class NetWithError(fluid.dygraph.layers.Layer): - @declarative + @to_static def forward(self, x): linear = paddle.nn.Linear(32, 64) y = linear(x) diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_ptb_lm.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_ptb_lm.py index 07600f738de..1ddd8e7065f 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_ptb_lm.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_ptb_lm.py @@ -23,7 +23,7 @@ import paddle.fluid as fluid from paddle.fluid.dygraph.base import to_variable from paddle.fluid.optimizer import SGDOptimizer from paddle.jit import ProgramTranslator -from paddle.jit.api import declarative +from paddle.jit.api import to_static PRINT_STEP = 20 SEED = 2020 @@ -186,7 +186,7 @@ class PtbModel(fluid.Layer): def build_once(self, input, label, init_hidden, init_cell): pass - @declarative + @to_static def forward(self, input, label, init_hidden, init_cell): init_h = paddle.reshape( diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_reinforcement_learning.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_reinforcement_learning.py index 4816e6ea6ef..3eeb6f16912 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_reinforcement_learning.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_reinforcement_learning.py @@ -24,7 +24,7 @@ import paddle.fluid as fluid import paddle.nn.functional as F from paddle.fluid.dygraph import Layer, to_variable from paddle.jit import ProgramTranslator -from paddle.jit.api import declarative +from paddle.jit.api import to_static SEED = 2020 program_translator = ProgramTranslator() @@ -41,7 +41,7 @@ class Policy(Layer): self.saved_log_probs = [] self.rewards = [] - @declarative + @to_static def forward(self, x): x = paddle.reshape(x, shape=[1, 4]) x = self.affine1(x) diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_save_inference_model.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_save_inference_model.py index dfea94e6fce..721e56e4d64 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_save_inference_model.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_save_inference_model.py @@ -21,7 +21,7 @@ import numpy as np import paddle import paddle.fluid as fluid from paddle.jit import ProgramTranslator -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.jit.dy2static.partial_program import partial_program_from from paddle.jit.translated_layer import INFER_MODEL_SUFFIX, INFER_PARAMS_SUFFIX @@ -40,7 +40,7 @@ class SimpleFcLayer(fluid.dygraph.Layer): super().__init__() self._linear = paddle.nn.Linear(fc_size, fc_size) - @declarative + @to_static def forward(self, x): y = self._linear(x) z = self._linear(y) diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_se_resnet.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_se_resnet.py index 6a841b56f13..27922a0f26b 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_se_resnet.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_se_resnet.py @@ -26,7 +26,7 @@ import paddle import paddle.fluid as fluid from paddle.fluid.dygraph.base import to_variable from paddle.jit import ProgramTranslator -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.jit.translated_layer import INFER_MODEL_SUFFIX, INFER_PARAMS_SUFFIX from paddle.nn import BatchNorm, Linear @@ -321,7 +321,7 @@ class SeResNeXt(fluid.dygraph.Layer): ), ) - @declarative + @to_static def forward(self, inputs, label): if self.layers == 50 or self.layers == 101: y = self.conv0(inputs) diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_sentiment.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_sentiment.py index b971039d225..95cf1365cbc 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_sentiment.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_sentiment.py @@ -21,7 +21,7 @@ import paddle import paddle.fluid as fluid from paddle.fluid.dygraph import to_variable from paddle.jit import ProgramTranslator -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.nn import Embedding, Linear SEED = 2020 @@ -89,7 +89,7 @@ class CNN(fluid.dygraph.Layer): self._fc1_act = paddle.nn.Softmax() self._fc_prediction = Linear(self.fc_hid_dim, self.class_dim) - @declarative + @to_static def forward(self, inputs, label=None): emb = self.embedding(inputs) o_np_mask = (paddle.reshape(inputs, [-1, 1]) != self.dict_dim).astype( @@ -133,7 +133,7 @@ class BOW(fluid.dygraph.Layer): self._fc2 = Linear(self.hid_dim, self.fc_hid_dim) self._fc_prediction = Linear(self.fc_hid_dim, self.class_dim) - @declarative + @to_static def forward(self, inputs, label=None): emb = self.embedding(inputs) o_np_mask = (paddle.reshape(inputs, [-1, 1]) != self.dict_dim).astype( @@ -182,7 +182,7 @@ class GRU(fluid.dygraph.Layer): self._fc_prediction = Linear(self.fc_hid_dim, self.class_dim) self._gru = DynamicGRU(size=self.hid_dim, h_0=h_0) - @declarative + @to_static def forward(self, inputs, label=None): emb = self.embedding(inputs) o_np_mask = (paddle.reshape(inputs, [-1, 1]) != self.dict_dim).astype( @@ -235,7 +235,7 @@ class BiGRU(fluid.dygraph.Layer): size=self.hid_dim, h_0=h_0, is_reverse=True ) - @declarative + @to_static def forward(self, inputs, label=None): emb = self.embedding(inputs) o_np_mask = (paddle.reshape(inputs, [-1, 1]) != self.dict_dim).astype( diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_tensor_shape.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_tensor_shape.py index 1ad55d3fbaa..116a2d7c68d 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_tensor_shape.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_tensor_shape.py @@ -18,7 +18,6 @@ import numpy as np import paddle import paddle.fluid as fluid -from paddle.jit.api import declarative def dyfunc_tensor_shape_1(x): @@ -252,7 +251,9 @@ class TestTensorShapeBasic(unittest.TestCase): def _run(self, to_static): with fluid.dygraph.guard(): if to_static: - res = declarative(self.dygraph_func)(self.input).numpy() + res = paddle.jit.to_static(self.dygraph_func)( + self.input + ).numpy() else: res = self.dygraph_func(self.input).numpy() return res diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_tsm.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_tsm.py index 6354e5a44a7..5e0c971c6ca 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_tsm.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_tsm.py @@ -25,7 +25,7 @@ import paddle import paddle.fluid as fluid from paddle.fluid.dygraph import to_variable from paddle.jit import ProgramTranslator -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.nn import BatchNorm, Linear random.seed(0) @@ -200,7 +200,7 @@ class TSM_ResNet(fluid.dygraph.Layer): ), ) - @declarative + @to_static def forward(self, inputs): y = paddle.reshape(inputs, [-1] + self.reshape_list) y = self.conv(y) diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_typehint.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_typehint.py index 2283c77bfb8..22ef8d00f1f 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_typehint.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_typehint.py @@ -16,8 +16,8 @@ import unittest import numpy as np +import paddle import paddle.fluid as fluid -from paddle.jit.api import declarative SEED = 2020 np.random.seed(SEED) @@ -56,7 +56,7 @@ class TestTransformWhileLoop(unittest.TestCase): # Set the input of dyfunc to VarBase tensor_x = fluid.dygraph.to_variable(self.x, zero_copy=False) if to_static: - ret = declarative(self.dyfunc)(tensor_x) + ret = paddle.jit.to_static(self.dyfunc)(tensor_x) else: ret = self.dyfunc(tensor_x) if hasattr(ret, "numpy"): diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_word2vec.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_word2vec.py index e546e26a230..61150231c57 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_word2vec.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_word2vec.py @@ -21,7 +21,7 @@ import numpy as np import paddle import paddle.fluid as fluid from paddle.jit import ProgramTranslator -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.nn import Embedding @@ -250,7 +250,7 @@ class SkipGram(fluid.dygraph.Layer): ), ) - @declarative + @to_static def forward(self, center_words, target_words, label): center_words_emb = self.embedding(center_words) target_words_emb = self.embedding_out(target_words) diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/yolov3.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/yolov3.py index 934c7923629..10df42faa23 100644 --- a/python/paddle/fluid/tests/unittests/dygraph_to_static/yolov3.py +++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/yolov3.py @@ -22,7 +22,7 @@ import paddle.fluid as fluid from paddle import _legacy_C_ops from paddle.fluid.param_attr import ParamAttr from paddle.fluid.regularizer import L2Decay -from paddle.jit.api import declarative +from paddle.jit.api import to_static class AttrDict(dict): @@ -277,7 +277,7 @@ class YOLOv3(fluid.dygraph.Layer): self.route_blocks_2.append(route) self.upsample = Upsample() - @declarative + @to_static def forward( self, inputs, diff --git a/python/paddle/fluid/tests/unittests/test_jit_save_load.py b/python/paddle/fluid/tests/unittests/test_jit_save_load.py index 2b2bfabd360..0ae577bc43d 100644 --- a/python/paddle/fluid/tests/unittests/test_jit_save_load.py +++ b/python/paddle/fluid/tests/unittests/test_jit_save_load.py @@ -25,7 +25,7 @@ import paddle import paddle.fluid as fluid from paddle.fluid import unique_name from paddle.fluid.layers.utils import flatten -from paddle.jit.api import declarative +from paddle.jit.api import to_static from paddle.jit.translated_layer import INFER_PARAMS_INFO_SUFFIX from paddle.nn import Linear from paddle.static import InputSpec @@ -57,7 +57,7 @@ class LinearNet(fluid.dygraph.Layer): super().__init__() self._linear = Linear(in_size, out_size) - @declarative + @to_static def forward(self, x): return self._linear(x) @@ -67,7 +67,7 @@ class LinearNetWithInputSpec(fluid.dygraph.Layer): super().__init__() self._linear = Linear(in_size, out_size) - @declarative(input_spec=[InputSpec(shape=[None, 784], dtype='float32')]) + @to_static(input_spec=[InputSpec(shape=[None, 784], dtype='float32')]) def forward(self, x): return self._linear(x) @@ -86,7 +86,7 @@ class LinerNetWithLabel(paddle.nn.Layer): super().__init__() self._linear = Linear(in_size, out_size) - @declarative( + @to_static( input_spec=[ InputSpec(shape=[None, 784], dtype='float32', name="image"), InputSpec(shape=[None, 1], dtype='int64', name="label"), @@ -106,7 +106,7 @@ class LinerNetWithPruneInput(paddle.nn.Layer): super().__init__() self._linear = Linear(in_size, out_size) - @declarative( + @to_static( input_spec=[ InputSpec(shape=[None, 784], dtype='float32', name="image"), InputSpec(shape=[None, 1], dtype='int64', name="label"), @@ -126,7 +126,7 @@ class LinerNetWithUselessInput(paddle.nn.Layer): super().__init__() self._linear = Linear(in_size, out_size) - @declarative( + @to_static( input_spec=[ InputSpec(shape=[None, 784], dtype='float32', name="image"), InputSpec(shape=[None, 1], dtype='int64', name="label"), @@ -142,7 +142,7 @@ class LinearNetReturnLoss(fluid.dygraph.Layer): super().__init__() self._linear = Linear(in_size, out_size) - @declarative + @to_static def forward(self, x): y = self._linear(x) z = self._linear(y) @@ -156,7 +156,7 @@ class LinearNetMultiInput(fluid.dygraph.Layer): self._linear1 = Linear(in_size, out_size) self._linear2 = Linear(in_size, out_size) - @declarative( + @to_static( input_spec=[ InputSpec([None, 8], dtype='float32'), InputSpec([None, 8], dtype='float32'), @@ -175,7 +175,7 @@ class LinearNetMultiInput1(fluid.dygraph.Layer): self._linear1 = Linear(in_size, out_size) self._linear2 = Linear(in_size, out_size) - @declarative( + @to_static( input_spec=( InputSpec([None, 8], dtype='float32'), InputSpec([None, 8], dtype='float32'), @@ -195,7 +195,7 @@ class MultiLoadingLinearNet(fluid.dygraph.Layer): self._load_linear1 = paddle.jit.load(model_path) self._load_linear2 = paddle.jit.load(model_path) - @declarative + @to_static def forward(self, x): tmp1 = self._linear(x) tmp2 = self._load_linear1(tmp1) @@ -210,7 +210,7 @@ class LinearNetReturnHidden(fluid.dygraph.Layer): self._linear_1 = Linear(in_size, out_size) self._linear_2 = Linear(in_size, out_size) - @declarative + @to_static def forward(self, x): y = self._linear_1(x) z = self._linear_2(y) @@ -224,7 +224,7 @@ class LinearNetWithNestOut(fluid.dygraph.Layer): self._linear_1 = Linear(in_size, out_size) self._linear_2 = Linear(in_size, out_size) - @declarative + @to_static def forward(self, x): y = self._linear_1(x) z = self._linear_2(y) @@ -456,7 +456,7 @@ class TestSaveLoadWithNestOut(unittest.TestCase): net = LinearNetWithNestOut(8, 8) dy_outs = flatten(net(x)) - net = declarative(net, input_spec=[InputSpec([None, 8], name='x')]) + net = to_static(net, input_spec=[InputSpec([None, 8], name='x')]) model_path = os.path.join(self.temp_dir.name, "net_with_nest_out/model") paddle.jit.save(net, model_path) @@ -549,7 +549,7 @@ class TestSaveLoadWithInputSpec(unittest.TestCase): def test_with_input_spec(self): net = LinearNetReturnLoss(8, 8) # set x.shape = [None, 8] - net.forward = declarative( + net.forward = to_static( net.forward, input_spec=[InputSpec([None, 8], name='x')] ) diff --git a/python/paddle/jit/__init__.py b/python/paddle/jit/__init__.py index c907efc02d1..fd5ca115c2e 100644 --- a/python/paddle/jit/__init__.py +++ b/python/paddle/jit/__init__.py @@ -15,7 +15,7 @@ from .api import save from .api import load -from .api import declarative as to_static +from .api import to_static from .api import not_to_static from .dy2static.logging_utils import set_code_level, set_verbosity diff --git a/python/paddle/jit/api.py b/python/paddle/jit/api.py index df555f6a244..b6ec7012634 100644 --- a/python/paddle/jit/api.py +++ b/python/paddle/jit/api.py @@ -178,7 +178,7 @@ def copy_decorator_attrs(original_func, decorated_obj): original_func(callable): the original decorated function. decorated_obj(StaticFunction): the target decorated StaticFunction object. """ - decorator_name = "declarative" + decorator_name = "to_static" decorated_obj.__name__ = original_func.__name__ decorated_obj._decorator_name = decorator_name @@ -190,12 +190,12 @@ def copy_decorator_attrs(original_func, decorated_obj): return decorated_obj -def declarative( +def to_static( function=None, input_spec=None, build_strategy=None, property=False ): """ Converts imperative dygraph APIs into declarative function APIs. Decorator - @declarative handles the Program and Executor of static mode and returns + @to_static handles the Program and Executor of static mode and returns the result as dygraph Tensor(s). Users could use the returned dygraph Tensor(s) to do imperative training, inference, or other operations. If the decorated function calls other imperative function, the called one will be @@ -264,7 +264,7 @@ def declarative( ) ) - # for usage: `declarative(foo, ...)` + # for usage: `to_static(foo, ...)` if function is not None: if isinstance(function, Layer): if isinstance(function.forward, StaticFunction): @@ -279,7 +279,7 @@ def declarative( else: return decorated(function) - # for usage: `@declarative` + # for usage: `@to_static` return decorated @@ -1008,7 +1008,7 @@ def save(layer, path, input_spec=None, **configs): inner_input_spec = pack_sequence_as( input_spec, inner_input_spec ) - static_forward = declarative( + static_forward = to_static( inner_layer.forward, input_spec=inner_input_spec ) concrete_program = ( @@ -1017,7 +1017,7 @@ def save(layer, path, input_spec=None, **configs): ) ) # the input_spec has been used in declarative, which is equal to - # @declarative with input_spec and jit.save without input_spec, + # @to_static with input_spec and jit.save without input_spec, # avoid needless warning inner_input_spec = None else: @@ -1041,7 +1041,7 @@ def save(layer, path, input_spec=None, **configs): inner_input_spec = pack_sequence_as( input_spec, inner_input_spec ) - static_function = declarative( + static_function = to_static( attr_func, input_spec=inner_input_spec ) concrete_program = static_function.concrete_program diff --git a/python/paddle/jit/dy2static/convert_call_func.py b/python/paddle/jit/dy2static/convert_call_func.py index 3a611a99390..26264840f26 100644 --- a/python/paddle/jit/dy2static/convert_call_func.py +++ b/python/paddle/jit/dy2static/convert_call_func.py @@ -241,12 +241,12 @@ def convert_call(func): if func.__name__ == '': return func try: - # Note(Aurelius84): Because `@declarative` returns a class instance instead of + # Note(Aurelius84): Because `@to_static` returns a class instance instead of # a function. This will modify the value referring to itself in `__globals__`. # For example: # - # @declarative + # @to_static # def foo(x): # return x # diff --git a/python/paddle/jit/dy2static/partial_program.py b/python/paddle/jit/dy2static/partial_program.py index 7554611ba21..40f276d269f 100644 --- a/python/paddle/jit/dy2static/partial_program.py +++ b/python/paddle/jit/dy2static/partial_program.py @@ -132,7 +132,7 @@ def _change_is_test_status(program, is_test): class PartialProgramLayer: """ - PartialProgramLayer wraps all the ops from layers decorated by `@declarative` + PartialProgramLayer wraps all the ops from layers decorated by `@to_static` and execute them as a static subgraph. .. note:: @@ -143,8 +143,8 @@ class PartialProgramLayer: Args: main_program(Program): The main program that contains ops need to be executed. - inputs(list[Variable]): The input list of the decorated function by `@declarative`. - outputs(list[Variable]): The output list of the decorated function by `@declarative`. + inputs(list[Variable]): The input list of the decorated function by `@to_static`. + outputs(list[Variable]): The output list of the decorated function by `@to_static`. parameters(list[VarBase]|None): All trainable parameters included in the program. Default None. Returns: @@ -534,7 +534,7 @@ class PartialProgramLayer: def _prune_unused_params(self, program): """ Prune the parameters not used anywhere in the program. - The `@declarative` may only decorated a sub function which + The `@to_static` may only decorated a sub function which contains some unused parameters created in `__init__`. So prune these parameters to avoid unnecessary operations in `run_program_op`. -- GitLab