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未验证 提交 2efcb481 编写于 作者: P pangyoki 提交者： GitHub
浏览文件
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Paddle-2.0 API directory migration (#25898) 

* Directory migration, test=develop

* Change imperative from paddle init to paddle framework, test=develop

* Fixed jit bug, test=develop

* default static mode, test=develop

* fixed format and create parameter belongs to framework, test=develop

* Fixed import package, test=develop

* fix __init__ format, test=develop

* fixed alias problem

* fixed paddle.enable_imperative problems, test=develop

* Add unittest

* delete install_check comment

* Fixed unittest timeout

* fixed unittest error

* move Program default_xx_program to static package

* optimize unittest method

* fixed framework __init__ format

* fixed jit path

* delete alias

* move jit to paddle

* Fixed unittest format

* fixed paddle.default_main_program

* Fixed save load API in paddle __init__.py

* fixed ci paddle.imperative.to_variable
上级 cd7b55a2
隐藏空白更改
内联 并排
Showing with 726 addition and 457 deletion
python/paddle/__init__.py
浏览文件 @ 2efcb481
......@@ -38,7 +38,6 @@ import paddle.tensor
import paddle.nn
import paddle.fleet
import paddle.framework
import paddle.imperative
import paddle.optimizer
import paddle.metric
import paddle.incubate.complex as complex
......@@ -69,8 +68,6 @@ from .tensor.creation import full_like #DEFINE_ALIAS
from .tensor.creation import triu #DEFINE_ALIAS
from .tensor.creation import tril #DEFINE_ALIAS
from .tensor.creation import meshgrid #DEFINE_ALIAS
from .tensor.io import save #DEFINE_ALIAS
from .tensor.io import load #DEFINE_ALIAS
from .tensor.linalg import matmul #DEFINE_ALIAS
from .tensor.linalg import dot #DEFINE_ALIAS
# from .tensor.linalg import einsum #DEFINE_ALIAS
......@@ -201,30 +198,34 @@ from .tensor.search import index_select #DEFINE_ALIAS
from .tensor.search import nonzero #DEFINE_ALIAS
from .tensor.search import sort #DEFINE_ALIAS
from .framework.random import manual_seed #DEFINE_ALIAS
from .framework import append_backward #DEFINE_ALIAS
from .framework import gradients #DEFINE_ALIAS
from .framework import Executor #DEFINE_ALIAS
from .framework import global_scope #DEFINE_ALIAS
from .framework import scope_guard #DEFINE_ALIAS
from .framework import BuildStrategy #DEFINE_ALIAS
from .framework import CompiledProgram #DEFINE_ALIAS
from .framework import default_main_program #DEFINE_ALIAS
from .framework import default_startup_program #DEFINE_ALIAS
from .framework import Variable #DEFINE_ALIAS
from .framework import ParamAttr #DEFINE_ALIAS
from .framework import create_global_var #DEFINE_ALIAS
from .framework import create_parameter #DEFINE_ALIAS
from .framework import Print #DEFINE_ALIAS
from .framework import py_func #DEFINE_ALIAS
from .framework import ExecutionStrategy #DEFINE_ALIAS
from .framework import name_scope #DEFINE_ALIAS
from .framework import ParallelExecutor #DEFINE_ALIAS
from .framework import ParamAttr #DEFINE_ALIAS
from .framework import Program #DEFINE_ALIAS
from .framework import program_guard #DEFINE_ALIAS
from .framework import Variable #DEFINE_ALIAS
from .framework import WeightNormParamAttr #DEFINE_ALIAS
from .framework import CPUPlace #DEFINE_ALIAS
from .framework import CUDAPlace #DEFINE_ALIAS
from .framework import CUDAPinnedPlace #DEFINE_ALIAS
from .framework import BackwardStrategy #DEFINE_ALIAS
from .framework import to_variable #DEFINE_ALIAS
from .framework import grad #DEFINE_ALIAS
from .framework import no_grad #DEFINE_ALIAS
from .framework import save_dygraph #DEFINE_ALIAS
from .framework import load_dygraph #DEFINE_ALIAS
from .framework import save #DEFINE_ALIAS
from .framework import load #DEFINE_ALIAS
from .framework import prepare_context #DEFINE_ALIAS
from .framework import ParallelEnv #DEFINE_ALIAS
from .framework import DataParallel #DEFINE_ALIAS
from .framework import NoamDecay #DEFINE_ALIAS
from .framework import PiecewiseDecay #DEFINE_ALIAS
from .framework import NaturalExpDecay #DEFINE_ALIAS
from .framework import ExponentialDecay #DEFINE_ALIAS
from .framework import InverseTimeDecay #DEFINE_ALIAS
from .framework import PolynomialDecay #DEFINE_ALIAS
from .framework import CosineDecay #DEFINE_ALIAS
from .tensor.search import index_sample #DEFINE_ALIAS
from .tensor.stat import mean #DEFINE_ALIAS
from .tensor.stat import reduce_mean #DEFINE_ALIAS
......@@ -237,6 +238,11 @@ from .fluid.data import data
from . import incubate
from .incubate import hapi
from .fluid.dygraph.base import enable_dygraph as enable_imperative #DEFINE_ALIAS
from .fluid.dygraph.base import disable_dygraph as disable_imperative #DEFINE_ALIAS
from .fluid.framework import in_dygraph_mode as in_imperative_mode #DEFINE_ALIAS
from .fluid.dygraph.base import enable_dygraph #DEFINE_ALIAS
from .fluid.dygraph.base import disable_dygraph #DEFINE_ALIAS
from .fluid.dygraph.base import enable_dygraph as disable_static #DEFINE_ALIAS
from .fluid.dygraph.base import disable_dygraph as enable_static #DEFINE_ALIAS
from .fluid.framework import in_dygraph_mode as in_dynamic_mode #DEFINE_ALIAS
from . import jit
from . import static
python/paddle/fleet/base/fleet_base.py
浏览文件 @ 2efcb481
......@@ -286,8 +286,8 @@ class Fleet(object):
context["loss"] = loss
if startup_program == None:
self.origin_startup_program = \
paddle.default_startup_program().clone(for_test=False)
startup_program = paddle.default_startup_program()
paddle.static.default_startup_program().clone(for_test=False)
startup_program = paddle.static.default_startup_program()
else:
self.origin_startup_program = \
startup_program.clone(for_test=False)
......@@ -338,7 +338,7 @@ class Fleet(object):
parameter_list=parameter_list,
no_grad_set=no_grad_set)
default_program = paddle.default_main_program()
default_program = paddle.static.default_main_program()
if id(default_program) != id(loss.block.program):
paddle.fluid.framework.switch_main_program(loss.block.program)
......
python/paddle/fleet/meta_optimizers/graph_execution_optimizer.py
浏览文件 @ 2efcb481
......@@ -190,7 +190,7 @@ class GraphExecutionOptimizer(MetaOptimizerBase):
parameter_list=None,
no_grad_set=None):
if startup_program == None:
startup_program = paddle.default_startup_program()
startup_program = paddle.static.default_startup_program()
compiled_program = self._try_to_compile(startup_program,
loss.block.program, loss)
loss.block.program._graph = compiled_program
......
python/paddle/fluid/dygraph/base.py
浏览文件 @ 2efcb481
......@@ -121,10 +121,6 @@ def enabled():
def enable_dygraph(place=None):
"""
:alias_main: paddle.enable_dygraph
:alias: paddle.enable_dygraph,paddle.enable_imperative.enable_dygraph
:old_api: paddle.fluid.dygraph.base.enable_dygraph
This function enables dynamic graph mode.
Parameters:
......@@ -155,10 +151,6 @@ def enable_dygraph(place=None):
def disable_dygraph():
"""
:alias_main: paddle.disable_dygraph
:alias: paddle.disable_dygraph,paddle.disable_imperative.disable_dygraph
:old_api: paddle.fluid.dygraph.base.disable_dygraph
This function disables dynamic graph mode.
return:
......
python/paddle/fluid/dygraph/jit.py
浏览文件 @ 2efcb481
......@@ -701,11 +701,11 @@ def save(layer, model_path, input_spec=None, configs=None):
prog_translator = ProgramTranslator()
if not prog_translator.enable:
raise RuntimeError(
"The paddle.imperative.jit.save doesn't work when setting ProgramTranslator.enable=False."
"The paddle.jit.save doesn't work when setting ProgramTranslator.enable=False."
)
if not isinstance(layer, Layer):
raise TypeError(
"The input layer of paddle.imperative.jit.save should be 'Layer', but received layer type is %s."
"The input layer of paddle.jit.save should be 'Layer', but received layer type is %s."
% type(layer))
if configs is None:
......
python/paddle/fluid/dygraph/layers.py
浏览文件 @ 2efcb481
......@@ -146,7 +146,7 @@ class Layer(core.Layer):
import paddle
import paddle.nn as nn
paddle.enable_imperative()
paddle.disable_static()
net = nn.Sequential(nn.Linear(2, 2), nn.Linear(2, 2))
......
python/paddle/fluid/dygraph/nn.py
浏览文件 @ 2efcb481
......@@ -3207,12 +3207,12 @@ class Flatten(layers.Layer):
.. code-block:: python
import paddle
from paddle.imperative import to_variable
from paddle import to_variable
import numpy as np
inp_np = np.ones([5, 2, 3, 4]).astype('float32')
paddle.enable_imperative()
paddle.disable_static()
inp_np = to_variable(inp_np)
flatten = paddle.nn.Flatten(start_axis=1, stop_axis=2)
......
python/paddle/fluid/dygraph/varbase_patch_methods.py
浏览文件 @ 2efcb481
......@@ -226,7 +226,7 @@ def monkey_patch_varbase():
.. code-block:: python
import paddle
paddle.enable_imperative()
paddle.disable_static()
x = paddle.rand([1, 5])
print(x)
# Variable: eager_tmp_0
......@@ -235,7 +235,7 @@ def monkey_patch_varbase():
# - layout: NCHW
# - dtype: float
# - data: [0.645307 0.597973 0.732793 0.646921 0.540328]
paddle.disable_imperative()
paddle.enable_static()
"""
tensor = self.value().get_tensor()
if tensor._is_initialized():
......
python/paddle/fluid/framework.py
浏览文件 @ 2efcb481
......@@ -5175,7 +5175,7 @@ class ParamBase(core.VarBase):
.. code-block:: python
import paddle
paddle.enable_imperative()
paddle.disable_static()
conv = paddle.nn.Conv2D(3, 3, 5)
print(conv.weight)
# Parameter: conv2d_0.w_0
......@@ -5184,7 +5184,7 @@ class ParamBase(core.VarBase):
# - layout: NCHW
# - dtype: float
# - data: [...]
paddle.disable_imperative()
paddle.enable_static()
"""
tensor = self.value().get_tensor()
if tensor._is_initialized():
......
python/paddle/fluid/install_check.py
浏览文件 @ 2efcb481
......@@ -13,6 +13,7 @@
# limitations under the License.
import os
import paddle
from .framework import Program, program_guard, unique_name, cuda_places, cpu_places
from .param_attr import ParamAttr
from .initializer import Constant
......
python/paddle/fluid/io.py
浏览文件 @ 2efcb481
......@@ -1669,9 +1669,6 @@ def _load_persistable_nodes(executor, dirname, graph):
def save(program, model_path):
"""
:api_attr: Static Graph
:alias_main: paddle.save
:alias: paddle.save,paddle.tensor.save,paddle.tensor.io.save
:old_api: paddle.fluid.save
This function save parameters, optimizer information and network description to model_path.
......@@ -1733,9 +1730,6 @@ def save(program, model_path):
def load(program, model_path, executor=None, var_list=None):
"""
:api_attr: Static Graph
:alias_main: paddle.load
:alias: paddle.load,paddle.tensor.load,paddle.tensor.io.load
:old_api: paddle.fluid.io.load
This function get parameters and optimizer information from program, and then get corresponding value from file.
An exception will throw if shape or dtype of the parameters is not match.
......
python/paddle/fluid/layers/nn.py
浏览文件 @ 2efcb481
......@@ -12073,11 +12073,11 @@ def logical_and(x, y, out=None, name=None):
import paddle
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
x_data = np.array([True, True, False, False], dtype=np.bool)
y_data = np.array([True, False, True, False], dtype=np.bool)
x = paddle.imperative.to_variable(x_data)
y = paddle.imperative.to_variable(y_data)
x = paddle.to_variable(x_data)
y = paddle.to_variable(y_data)
res = paddle.logical_and(x, y)
print(res.numpy()) # [True False False False]
"""
......@@ -12115,11 +12115,11 @@ def logical_or(x, y, out=None, name=None):
import paddle
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
x_data = np.array([True, True, False, False], dtype=np.bool)
y_data = np.array([True, False, True, False], dtype=np.bool)
x = paddle.imperative.to_variable(x_data)
y = paddle.imperative.to_variable(y_data)
x = paddle.to_variable(x_data)
y = paddle.to_variable(y_data)
res = paddle.logical_or(x, y)
print(res.numpy()) # [True True True False]
"""
......@@ -12157,11 +12157,11 @@ def logical_xor(x, y, out=None, name=None):
import paddle
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
x_data = np.array([True, True, False, False], dtype=np.bool)
y_data = np.array([True, False, True, False], dtype=np.bool)
x = paddle.imperative.to_variable(x_data)
y = paddle.imperative.to_variable(y_data)
x = paddle.to_variable(x_data)
y = paddle.to_variable(y_data)
res = paddle.logical_xor(x, y)
print(res.numpy()) # [False True True False]
"""
......@@ -12197,9 +12197,9 @@ def logical_not(x, out=None, name=None):
import paddle
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
x_data = np.array([True, False, True, False], dtype=np.bool)
x = paddle.imperative.to_variable(x_data)
x = paddle.to_variable(x_data)
res = paddle.logical_not(x)
print(res.numpy()) # [False True False True]
"""
......
python/paddle/fluid/tests/unittests/test_arange.py
浏览文件 @ 2efcb481
......@@ -16,7 +16,7 @@ from __future__ import print_function
import paddle
from paddle.fluid import core
from paddle import program_guard, Program
from paddle.static import program_guard, Program
import unittest
import numpy as np
from op_test import OpTest
......@@ -82,7 +82,7 @@ class TestArangeAPI(unittest.TestCase):
place = paddle.CUDAPlace(0) if core.is_compiled_with_cuda(
) else paddle.CPUPlace()
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
out = exe.run(fetch_list=[x1])
expected_data = np.arange(0, 5, 1).astype(np.float32)
......@@ -93,15 +93,16 @@ class TestArangeImperative(unittest.TestCase):
def test_out(self):
place = paddle.CUDAPlace(0) if core.is_compiled_with_cuda(
) else paddle.CPUPlace()
with paddle.imperative.guard(place):
x1 = paddle.arange(0, 5, 1)
x2 = paddle.tensor.arange(5)
x3 = paddle.tensor.creation.arange(5)
start = paddle.imperative.to_variable(np.array([0], 'float32'))
end = paddle.imperative.to_variable(np.array([5], 'float32'))
step = paddle.imperative.to_variable(np.array([1], 'float32'))
x4 = paddle.arange(start, end, step, 'int64')
paddle.disable_static(place)
x1 = paddle.arange(0, 5, 1)
x2 = paddle.tensor.arange(5)
x3 = paddle.tensor.creation.arange(5)
start = paddle.to_variable(np.array([0], 'float32'))
end = paddle.to_variable(np.array([5], 'float32'))
step = paddle.to_variable(np.array([1], 'float32'))
x4 = paddle.arange(start, end, step, 'int64')
paddle.enable_static()
expected_data = np.arange(0, 5, 1).astype(np.int64)
for i in [x1, x2, x3, x4]:
......
python/paddle/fluid/tests/unittests/test_argsort_op.py
浏览文件 @ 2efcb481
......@@ -17,7 +17,6 @@ from __future__ import print_function
import unittest
import paddle
import paddle.fluid as fluid
import paddle.imperative as imperative
import paddle.fluid.layers as layers
import numpy as np
import six
......@@ -384,20 +383,21 @@ class TestArgsortDygraph(unittest.TestCase):
self.place = core.CPUPlace()
def test_api_0(self):
with imperative.guard(self.place):
var_x = imperative.to_variable(self.input_data)
out = paddle.argsort(var_x)
self.assertEqual((np.argsort(self.input_data) == out.numpy()).all(),
True)
paddle.disable_static(self.place)
var_x = paddle.to_variable(self.input_data)
out = paddle.argsort(var_x)
self.assertEqual((np.argsort(self.input_data) == out.numpy()).all(),
True)
paddle.enable_static()
def test_api_1(self):
with imperative.guard(self.place):
var_x = imperative.to_variable(self.input_data)
out = paddle.argsort(var_x, axis=-1)
self.assertEqual(
(np.argsort(
self.input_data, axis=-1) == out.numpy()).all(),
True)
paddle.disable_static(self.place)
var_x = paddle.to_variable(self.input_data)
out = paddle.argsort(var_x, axis=-1)
self.assertEqual(
(np.argsort(
self.input_data, axis=-1) == out.numpy()).all(), True)
paddle.enable_static()
if __name__ == "__main__":
......
python/paddle/fluid/tests/unittests/test_compare_op.py
浏览文件 @ 2efcb481
......@@ -97,7 +97,7 @@ def create_paddle_case(op_type, callback):
y = paddle.nn.data(name='y', shape=[1, 2, 3], dtype='int32')
op = eval("paddle.%s" % (self.op_type))
out = op(x, y)
exe = paddle.Executor(self.place)
exe = paddle.static.Executor(self.place)
input_x = np.arange(1, 7).reshape((1, 2, 1, 3)).astype(np.int32)
input_y = np.arange(0, 6).reshape((1, 2, 3)).astype(np.int32)
real_result = callback(input_x, input_y)
......
python/paddle/fluid/tests/unittests/test_concat_op.py
浏览文件 @ 2efcb481
......@@ -268,9 +268,9 @@ class TestConcatAPI(unittest.TestCase):
out_3 = paddle.concat(x=[x_2, x_3], axis=positive_1_int64)
out_4 = paddle.concat(x=[x_2, x_3], axis=negative_int64)
exe = paddle.Executor(place=paddle.CPUPlace())
exe = paddle.static.Executor(place=paddle.CPUPlace())
[res_1, res_2, res_3, res_4] = exe.run(
paddle.default_main_program(),
paddle.static.default_main_program(),
feed={"x_1": input_2,
"x_2": input_2,
"x_3": input_3},
......@@ -284,14 +284,15 @@ class TestConcatAPI(unittest.TestCase):
in1 = np.array([[1, 2, 3], [4, 5, 6]])
in2 = np.array([[11, 12, 13], [14, 15, 16]])
in3 = np.array([[21, 22], [23, 24]])
with paddle.imperative.guard():
x1 = paddle.imperative.to_variable(in1)
x2 = paddle.imperative.to_variable(in2)
x3 = paddle.imperative.to_variable(in3)
out1 = fluid.layers.concat(input=[x1, x2, x3], axis=-1)
out2 = paddle.concat(x=[x1, x2], axis=0)
np_out1 = np.concatenate([in1, in2, in3], axis=-1)
np_out2 = np.concatenate([in1, in2], axis=0)
paddle.disable_static()
x1 = paddle.to_variable(in1)
x2 = paddle.to_variable(in2)
x3 = paddle.to_variable(in3)
out1 = fluid.layers.concat(input=[x1, x2, x3], axis=-1)
out2 = paddle.concat(x=[x1, x2], axis=0)
np_out1 = np.concatenate([in1, in2, in3], axis=-1)
np_out2 = np.concatenate([in1, in2], axis=0)
paddle.enable_static()
self.assertEqual((out1.numpy() == np_out1).all(), True)
self.assertEqual((out2.numpy() == np_out2).all(), True)
......
python/paddle/fluid/tests/unittests/test_cumsum_op.py
浏览文件 @ 2efcb481
......@@ -21,7 +21,7 @@ import paddle
import paddle.fluid.core as core
import paddle.fluid as fluid
from paddle.fluid import compiler, Program, program_guard
from paddle.imperative import to_variable
from paddle import to_variable
class TestCumsumOp(unittest.TestCase):
......@@ -83,16 +83,18 @@ class TestCumsumOp(unittest.TestCase):
self.assertTrue(np.allclose(z, out[5]))
def test_cpu(self):
with paddle.imperative.guard(paddle.fluid.CPUPlace()):
self.run_cases()
paddle.disable_static(paddle.fluid.CPUPlace())
self.run_cases()
paddle.enable_static()
self.run_static()
def test_gpu(self):
if not fluid.core.is_compiled_with_cuda():
return
with paddle.imperative.guard(paddle.fluid.CUDAPlace(0)):
self.run_cases()
paddle.disable_static(paddle.fluid.CUDAPlace(0))
self.run_cases()
paddle.enable_static()
self.run_static(use_gpu=True)
......
python/paddle/fluid/tests/unittests/test_directory_migration.py 0 → 100644
浏览文件 @ 2efcb481
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import print_function
import os
import sys
import time
import subprocess
import unittest
import numpy as np
import paddle
class TestDirectory(unittest.TestCase):
def get_import_command(self, module):
paths = module.split('.')
if len(paths) <= 1:
return module
package = '.'.join(paths[:-1])
func = paths[-1]
cmd = 'from {} import {}'.format(package, func)
return cmd
def test_new_directory(self):
new_directory = [
'paddle.enable_static', 'paddle.disable_static',
'paddle.in_dynamic_mode', 'paddle.to_variable', 'paddle.grad',
'paddle.no_grad', 'paddle.save', 'paddle.load',
'paddle.static.save', 'paddle.static.load',
'paddle.BackwardStrategy', 'paddle.ParallelEnv',
'paddle.prepare_context', 'paddle.DataParallel', 'paddle.jit',
'paddle.jit.TracedLayer', 'paddle.jit.to_static',
'paddle.jit.ProgramTranslator', 'paddle.jit.TranslatedLayer',
'paddle.jit.save', 'paddle.jit.load', 'paddle.jit.SaveLoadConfig',
'paddle.NoamDecay', 'paddle.PiecewiseDecay',
'paddle.NaturalExpDecay', 'paddle.ExponentialDecay',
'paddle.InverseTimeDecay', 'paddle.PolynomialDecay',
'paddle.CosineDecay', 'paddle.static.Executor',
'paddle.static.global_scope', 'paddle.static.scope_guard',
'paddle.static.append_backward', 'paddle.static.gradients',
'paddle.static.BuildStrategy', 'paddle.static.CompiledProgram',
'paddle.static.ExecutionStrategy',
'paddle.static.default_main_program',
'paddle.static.default_startup_program', 'paddle.static.Program',
'paddle.static.name_scope', 'paddle.static.program_guard',
'paddle.static.Print', 'paddle.static.py_func',
'paddle.static.ParallelExecutor',
'paddle.static.WeightNormParamAttr', 'paddle.static.nn.fc',
'paddle.static.nn.batch_norm',
'paddle.static.nn.bilinear_tensor_product',
'paddle.static.nn.conv2d', 'paddle.static.nn.conv2d_transpose',
'paddle.static.nn.conv3d', 'paddle.static.nn.conv3d_transpose',
'paddle.static.nn.create_parameter',
'paddle.static.nn.crf_decoding', 'paddle.static.nn.data_norm',
'paddle.static.nn.deformable_conv', 'paddle.static.nn.group_norm',
'paddle.static.nn.hsigmoid', 'paddle.static.nn.instance_norm',
'paddle.static.nn.layer_norm', 'paddle.static.nn.multi_box_head',
'paddle.static.nn.nce', 'paddle.static.nn.prelu',
'paddle.static.nn.row_conv', 'paddle.static.nn.spectral_norm',
'paddle.static.nn.embedding'
]
import_file = 'run_import_modules.py'
with open(import_file, "w") as wb:
for module in new_directory:
run_cmd = self.get_import_command(module)
wb.write("{}\n".format(run_cmd))
_python = sys.executable
ps_cmd = "{} {}".format(_python, import_file)
ps_proc = subprocess.Popen(
ps_cmd.strip().split(" "),
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
stdout, stderr = ps_proc.communicate()
assert "Error" not in str(stderr), "Error: Can't" \
" import Module {}".format(module)
def test_old_directory(self):
old_directory = [
'paddle.enable_imperative', 'paddle.disable_imperative',
'paddle.in_imperative_mode', 'paddle.imperative.to_variable',
'paddle.imperative.enable', 'paddle.imperative.guard',
'paddle.imperative.grad', 'paddle.imperative.no_grad',
'paddle.imperative.save', 'paddle.imperative.load',
'paddle.imperative.BackwardStrategy',
'paddle.imperative.ParallelEnv',
'paddle.imperative.prepare_context',
'paddle.imperative.DataParalell', 'paddle.imperative.jit',
'paddle.imperative.TracedLayer', 'paddle.imperative.declarative',
'paddle.imperative.ProgramTranslator',
'paddle.imperative.TranslatedLayer', 'paddle.imperative.jit.save',
'paddle.imperative.jit.load',
'paddle.imperative.jit.SaveLoadConfig',
'paddle.imperative.NoamDecay'
'paddle.imperative.PiecewiseDecay',
'paddle.imperative.NaturalExpDecay',
'paddle.imperative.ExponentialDecay',
'paddle.imperative.InverseTimeDecay',
'paddle.imperative.PolynomialDecay',
'paddle.imperative.CosineDecay', 'paddle.Executor',
'paddle.global_scope', 'paddle.scope_guard',
'paddle.append_backward', 'paddle.gradients',
'paddle.BuildStrategy', 'paddle.CompiledProgram',
'paddle.ExecutionStrategy', 'paddle.name_scope',
'paddle.program_guard', 'paddle.Print', 'paddle.py_func',
'paddle.ParallelExecutor', 'paddle.default_main_program',
'paddle.default_startup_program', 'paddle.Program',
'paddle.WeightNormParamAttr', 'paddle.declarative.fc',
'paddle.declarative.batch_norm',
'paddle.declarative.bilinear_tensor_product',
'paddle.declarative.conv2d', 'paddle.declarative.conv2d_transpose',
'paddle.declarative.conv3d', 'paddle.declarative.conv3d_transpose',
'paddle.declarative.create_parameter',
'paddle.declarative.crf_decoding', 'paddle.declarative.data_norm',
'paddle.declarative.deformable_conv',
'paddle.declarative.group_norm', 'paddle.declarative.hsigmoid',
'paddle.declarative.instance_norm', 'paddle.declarative.layer_norm',
'paddle.declarative.multi_box_head', 'paddle.declarative.nce',
'paddle.declarative.prelu', 'paddle.declarative.row_conv',
'paddle.declarative.spectral_norm', 'paddle.declarative.embedding'
]
import_file = 'run_old_import_modules.py'
with open(import_file, "w") as wb:
cmd_context_count = """
count = 0
err_module = ""
"""
wb.write(cmd_context_count)
for module in old_directory:
run_cmd = self.get_import_command(module)
cmd_context_loop_template = """
try:
{run_cmd}
except:
count += 1
else:
err_module = "{module}"
"""
cmd_context_loop = cmd_context_loop_template.format(
run_cmd=run_cmd, module=module)
wb.write(cmd_context_loop)
cmd_context_print_template = """
if count != {len_old_directory}:
print("Error: Module " + err_module + " should not be imported")
"""
cmd_context_print = cmd_context_print_template.format(
len_old_directory=str(len(old_directory)))
wb.write(cmd_context_print)
_python = sys.executable
ps_cmd = "{} {}".format(_python, import_file)
ps_proc = subprocess.Popen(
ps_cmd.strip().split(" "),
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
stdout, stderr = ps_proc.communicate()
assert "Error" not in str(stdout), str(stdout)
if __name__ == '__main__':
unittest.main()
python/paddle/fluid/tests/unittests/test_eye_op.py
浏览文件 @ 2efcb481
......@@ -74,73 +74,70 @@ class TestEyeOp2(OpTest):
class API_TestTensorEye(unittest.TestCase):
def test_out(self):
with paddle.program_guard(paddle.Program()):
with paddle.static.program_guard(paddle.static.Program()):
data = paddle.eye(10)
place = fluid.CPUPlace()
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
result, = exe.run(fetch_list=[data])
expected_result = np.eye(10, dtype="float32")
self.assertEqual((result == expected_result).all(), True)
with paddle.program_guard(paddle.Program()):
with paddle.static.program_guard(paddle.static.Program()):
data = paddle.eye(10, num_columns=7, dtype="float64")
place = paddle.CPUPlace()
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
result, = exe.run(fetch_list=[data])
expected_result = np.eye(10, 7, dtype="float64")
self.assertEqual((result == expected_result).all(), True)
with paddle.program_guard(paddle.Program()):
with paddle.static.program_guard(paddle.static.Program()):
data = paddle.eye(10, dtype="int64")
place = paddle.CPUPlace()
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
result, = exe.run(fetch_list=[data])
expected_result = np.eye(10, dtype="int64")
self.assertEqual((result == expected_result).all(), True)
with paddle.imperative.guard():
out = paddle.eye(10, dtype="int64")
expected_result = np.eye(10, dtype="int64")
paddle.disable_static()
out = paddle.eye(10, dtype="int64")
expected_result = np.eye(10, dtype="int64")
paddle.enable_static()
self.assertEqual((out.numpy() == expected_result).all(), True)
with paddle.imperative.guard():
batch_shape = [2]
out = fluid.layers.eye(10,
10,
dtype="int64",
batch_shape=batch_shape)
result = np.eye(10, dtype="int64")
expected_result = []
for index in reversed(batch_shape):
tmp_result = []
for i in range(index):
tmp_result.append(result)
result = tmp_result
expected_result = np.stack(result, axis=0)
paddle.disable_static()
batch_shape = [2]
out = fluid.layers.eye(10, 10, dtype="int64", batch_shape=batch_shape)
result = np.eye(10, dtype="int64")
expected_result = []
for index in reversed(batch_shape):
tmp_result = []
for i in range(index):
tmp_result.append(result)
result = tmp_result
expected_result = np.stack(result, axis=0)
paddle.enable_static()
self.assertEqual(out.numpy().shape == np.array(expected_result).shape,
True)
self.assertEqual((out.numpy() == expected_result).all(), True)
with paddle.imperative.guard():
batch_shape = [3, 2]
out = fluid.layers.eye(10,
10,
dtype="int64",
batch_shape=batch_shape)
result = np.eye(10, dtype="int64")
expected_result = []
for index in reversed(batch_shape):
tmp_result = []
for i in range(index):
tmp_result.append(result)
result = tmp_result
expected_result = np.stack(result, axis=0)
paddle.disable_static()
batch_shape = [3, 2]
out = fluid.layers.eye(10, 10, dtype="int64", batch_shape=batch_shape)
result = np.eye(10, dtype="int64")
expected_result = []
for index in reversed(batch_shape):
tmp_result = []
for i in range(index):
tmp_result.append(result)
result = tmp_result
expected_result = np.stack(result, axis=0)
paddle.enable_static()
self.assertEqual(out.numpy().shape == np.array(expected_result).shape,
True)
self.assertEqual((out.numpy() == expected_result).all(), True)
def test_errors(self):
with paddle.program_guard(paddle.Program()):
with paddle.static.program_guard(paddle.static.Program()):
def test_num_rows_type_check():
paddle.eye(-1, dtype="int64")
......
python/paddle/fluid/tests/unittests/test_flatten_contiguous_range_op.py
浏览文件 @ 2efcb481
......@@ -191,8 +191,8 @@ class TestFlattenPython(unittest.TestCase):
self.assertRaises(ValueError, test_InputError)
def test_Negative():
paddle.enable_imperative()
img = paddle.imperative.to_variable(x)
paddle.disable_static()
img = paddle.to_variable(x)
out = paddle.flatten(img, start_axis=-2, stop_axis=-1)
return out.numpy().shape
......
python/paddle/fluid/tests/unittests/test_full_like_op.py
浏览文件 @ 2efcb481
......@@ -16,7 +16,7 @@ from __future__ import print_function
import paddle
import paddle.fluid.core as core
from paddle import Program, program_guard
from paddle.static import program_guard, Program
import paddle.compat as cpt
import unittest
import numpy as np
......@@ -38,7 +38,7 @@ class TestFullOp(unittest.TestCase):
place = paddle.CPUPlace()
if core.is_compiled_with_cuda():
place = paddle.CUDAPlace(0)
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
exe.run(startup_program)
img = np.array([[1, 2, 3], [4, 5, 6]]).astype(np.float32)
......@@ -53,12 +53,13 @@ class TestFullOp(unittest.TestCase):
msg="full_like output is wrong, out = " + str(out_np))
def test_full_like_imperative(self):
with paddle.imperative.guard():
input = paddle.arange(6, 10, dtype='float32')
out = paddle.full_like(input, fill_value=888.88, dtype='float32')
out_numpy = np.random.random((4)).astype("float32")
out_numpy.fill(888.88)
self.assertTrue((out.numpy() == out_numpy).all(), True)
paddle.disable_static()
input = paddle.arange(6, 10, dtype='float32')
out = paddle.full_like(input, fill_value=888.88, dtype='float32')
out_numpy = np.random.random((4)).astype("float32")
out_numpy.fill(888.88)
self.assertTrue((out.numpy() == out_numpy).all(), True)
paddle.enable_static()
class TestFullOpError(unittest.TestCase):
......
python/paddle/fluid/tests/unittests/test_imperative_basic.py
浏览文件 @ 2efcb481
......@@ -205,27 +205,28 @@ class TestImperative(unittest.TestCase):
self.assertTrue(np.array_equal(dy_grad1, dy_grad2))
def test_functional_paddle_imperative_dygraph_context(self):
self.assertFalse(paddle.imperative.enabled())
paddle.enable_imperative()
self.assertTrue(paddle.imperative.enabled())
self.assertFalse(paddle.in_dynamic_mode())
paddle.disable_static()
self.assertTrue(paddle.in_dynamic_mode())
np_inp = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32)
var_inp = paddle.imperative.to_variable(np_inp)
var_inp = paddle.to_variable(np_inp)
mlp = MLP(input_size=2)
out = mlp(var_inp)
dy_out1 = out.numpy()
out.backward()
dy_grad1 = mlp._linear1.weight.gradient()
paddle.disable_imperative()
self.assertFalse(paddle.imperative.enabled())
with paddle.imperative.guard():
self.assertTrue(paddle.imperative.enabled())
var_inp = paddle.imperative.to_variable(np_inp)
mlp = MLP(input_size=2)
out = mlp(var_inp)
dy_out2 = out.numpy()
out.backward()
dy_grad2 = mlp._linear1.weight.gradient()
self.assertFalse(paddle.imperative.enabled())
paddle.enable_static()
self.assertFalse(paddle.in_dynamic_mode())
paddle.disable_static()
self.assertTrue(paddle.in_dynamic_mode())
var_inp = paddle.to_variable(np_inp)
mlp = MLP(input_size=2)
out = mlp(var_inp)
dy_out2 = out.numpy()
out.backward()
dy_grad2 = mlp._linear1.weight.gradient()
paddle.enable_static()
self.assertFalse(paddle.in_dynamic_mode())
self.assertTrue(np.array_equal(dy_out1, dy_out2))
self.assertTrue(np.array_equal(dy_grad1, dy_grad2))
......@@ -281,7 +282,7 @@ class TestImperative(unittest.TestCase):
l0 = fluid.Linear(2, 2)
self.assertTrue(l0.weight._grad_ivar() is None)
l1 = fluid.Linear(2, 2)
with paddle.imperative.no_grad():
with paddle.no_grad():
self.assertTrue(l1.weight.stop_gradient is False)
tmp = l1.weight * 2
self.assertTrue(tmp.stop_gradient)
......
python/paddle/fluid/tests/unittests/test_imperative_data_parallel.py
浏览文件 @ 2efcb481
......@@ -43,7 +43,7 @@ class MLP(fluid.Layer):
class TestDataParallelStateDict(unittest.TestCase):
def test_data_parallel_state_dict(self):
with fluid.dygraph.guard():
strategy = paddle.imperative.prepare_context()
strategy = paddle.prepare_context()
mlp = MLP()
parallel_mlp = dygraph.parallel.DataParallel(mlp, strategy)
......
python/paddle/fluid/tests/unittests/test_imperative_mnist.py
浏览文件 @ 2efcb481
......@@ -153,7 +153,7 @@ class TestImperativeMnist(unittest.TestCase):
label.stop_gradient = True
if batch_id % 10 == 0:
cost, traced_layer = paddle.imperative.TracedLayer.trace(
cost, traced_layer = paddle.jit.TracedLayer.trace(
mnist, inputs=img)
if program is not None:
self.assertTrue(program, traced_layer.program)
......
python/paddle/fluid/tests/unittests/test_imperative_save_load.py
浏览文件 @ 2efcb481
......@@ -292,7 +292,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
np_t = v.numpy()
self.model_base[k] = np_t
paddle.imperative.save(self.state_dict, "./test_dy")
paddle.save(self.state_dict, "./test_dy")
def testLoadAndSetVarBase(self):
seed = 90
......@@ -373,8 +373,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
if isinstance(adam._learning_rate, LearningRateDecay):
adam._learning_rate.step_num = 0
para_state_dict, opti_state_dict = paddle.imperative.load(
"./test_dy")
para_state_dict, opti_state_dict = paddle.load("./test_dy")
adam.set_dict(opti_state_dict)
opti_dict = adam.state_dict()
......@@ -900,18 +899,17 @@ class TestDygraphPtbRnn(unittest.TestCase):
with fluid.dygraph.guard():
emb = fluid.dygraph.Embedding([10, 10])
state_dict = emb.state_dict()
paddle.imperative.save(state_dict,
os.path.join('saved_dy', 'emb_dy'))
paddle.save(state_dict, os.path.join('saved_dy', 'emb_dy'))
para_state_dict, opti_state_dict = paddle.imperative.load(
para_state_dict, opti_state_dict = paddle.load(
os.path.join('saved_dy', 'emb_dy'))
self.assertTrue(opti_state_dict == None)
para_state_dict, opti_state_dict = paddle.imperative.load(
para_state_dict, opti_state_dict = paddle.load(
os.path.join('saved_dy', 'emb_dy.pdparams'))
para_state_dict, opti_state_dict = paddle.imperative.load(
para_state_dict, opti_state_dict = paddle.load(
os.path.join('saved_dy', 'emb_dy.pdopt'))
......
python/paddle/fluid/tests/unittests/test_imperative_selected_rows.py
浏览文件 @ 2efcb481
......@@ -47,33 +47,34 @@ class TestSimpleNet(unittest.TestCase):
for place in places:
for dtype in ["float32", "float64"]:
for sort_sum_gradient in [True, False]:
with paddle.imperative.guard(place):
backward_strategy = paddle.imperative.BackwardStrategy()
backward_strategy.sort_sum_gradient = sort_sum_gradient
# grad_clip = fluid.clip.GradientClipByGlobalNorm(5.0)
paddle.disable_static(place)
backward_strategy = paddle.BackwardStrategy()
backward_strategy.sort_sum_gradient = sort_sum_gradient
# grad_clip = fluid.clip.GradientClipByGlobalNorm(5.0)
input_word = np.array([[1, 2], [2, 1]]).astype('int64')
input = paddle.imperative.to_variable(input_word)
input_word = np.array([[1, 2], [2, 1]]).astype('int64')
input = paddle.to_variable(input_word)
simplenet = SimpleNet(20, 32, dtype)
adam = SGDOptimizer(
learning_rate=0.001,
parameter_list=simplenet.parameters(
)) # grad_clip=grad_clip
input_emb, emb = simplenet(input)
simplenet = SimpleNet(20, 32, dtype)
adam = SGDOptimizer(
learning_rate=0.001,
parameter_list=simplenet.parameters(
)) # grad_clip=grad_clip
input_emb, emb = simplenet(input)
self.assertTrue(emb.weight.gradient() is None)
self.assertTrue(input_emb.gradient() is None)
self.assertTrue(emb.weight.gradient() is None)
self.assertTrue(input_emb.gradient() is None)
input_emb.backward(backward_strategy)
adam.minimize(input_emb)
self.assertTrue(emb.weight.gradient() is not None)
input_emb.backward(backward_strategy)
adam.minimize(input_emb)
self.assertTrue(emb.weight.gradient() is not None)
emb.clear_gradients()
self.assertTrue(emb.weight.gradient() is None)
emb.clear_gradients()
self.assertTrue(emb.weight.gradient() is None)
input_emb.clear_gradient()
self.assertTrue(input_emb.gradient() is not None)
input_emb.clear_gradient()
self.assertTrue(input_emb.gradient() is not None)
paddle.enable_static()
def test_selectedrows_gradient2(self):
places = [fluid.CPUPlace()]
......
python/paddle/fluid/tests/unittests/test_linspace.py
浏览文件 @ 2efcb481
......@@ -82,15 +82,16 @@ class TestLinspaceAPI(unittest.TestCase):
assert np.array_equal(res_1, res_2)
def test_name(self):
with paddle.program_guard(paddle.Program()):
with paddle.static.program_guard(paddle.static.Program()):
out = paddle.linspace(
0, 10, 5, dtype='float32', name='linspace_res')
assert 'linspace_res' in out.name
def test_imperative(self):
with paddle.imperative.guard():
out = paddle.linspace(0, 10, 5, dtype='float32')
np_out = np.linspace(0, 10, 5, dtype='float32')
paddle.disable_static()
out = paddle.linspace(0, 10, 5, dtype='float32')
np_out = np.linspace(0, 10, 5, dtype='float32')
paddle.enable_static()
self.assertEqual((out.numpy() == np_out).all(), True)
......
python/paddle/fluid/tests/unittests/test_multiply.py
浏览文件 @ 2efcb481
......@@ -41,9 +41,9 @@ class TestMultiplyAPI(unittest.TestCase):
return res
def __run_dynamic_graph_case(self, x_data, y_data, axis=-1):
paddle.enable_imperative()
x = paddle.imperative.to_variable(x_data)
y = paddle.imperative.to_variable(y_data)
paddle.disable_static()
x = paddle.to_variable(x_data)
y = paddle.to_variable(y_data)
res = paddle.multiply(x, y, axis=axis)
return res.numpy()
......@@ -107,7 +107,7 @@ class TestMultiplyError(unittest.TestCase):
def test_errors(self):
"""test_errors."""
# test static computation graph: dtype can not be int8
paddle.disable_imperative()
paddle.enable_static()
with program_guard(Program(), Program()):
x = paddle.nn.data(name='x', shape=[100], dtype=np.int8)
y = paddle.nn.data(name='y', shape=[100], dtype=np.int8)
......@@ -121,18 +121,18 @@ class TestMultiplyError(unittest.TestCase):
np.random.seed(7)
# test dynamic computation graph: dtype can not be int8
paddle.enable_imperative()
paddle.disable_static()
x_data = np.random.randn(200).astype(np.int8)
y_data = np.random.randn(200).astype(np.int8)
x = paddle.imperative.to_variable(x_data)
y = paddle.imperative.to_variable(y_data)
x = paddle.to_variable(x_data)
y = paddle.to_variable(y_data)
self.assertRaises(fluid.core.EnforceNotMet, paddle.multiply, x, y)
# test dynamic computation graph: inputs must be broadcastable
x_data = np.random.rand(200, 5)
y_data = np.random.rand(200)
x = paddle.imperative.to_variable(x_data)
y = paddle.imperative.to_variable(y_data)
x = paddle.to_variable(x_data)
y = paddle.to_variable(y_data)
self.assertRaises(fluid.core.EnforceNotMet, paddle.multiply, x, y)
......
python/paddle/fluid/tests/unittests/test_ones_like.py
浏览文件 @ 2efcb481
......@@ -62,18 +62,18 @@ class TestOnesLikeImpeartive(unittest.TestCase):
shape = [3, 4]
place = fluid.CUDAPlace(0) if core.is_compiled_with_cuda(
) else fluid.CPUPlace()
with paddle.imperative.guard(place):
x = paddle.imperative.to_variable(np.ones(shape))
for dtype in [np.bool, np.float32, np.float64, np.int32, np.int64]:
out = ones_like(x, dtype)
self.assertEqual((out.numpy() == np.ones(shape, dtype)).all(),
True)
out = paddle.tensor.ones_like(x)
paddle.disable_static(place)
x = paddle.to_variable(np.ones(shape))
for dtype in [np.bool, np.float32, np.float64, np.int32, np.int64]:
out = ones_like(x, dtype)
self.assertEqual((out.numpy() == np.ones(shape, dtype)).all(), True)
out = paddle.tensor.creation.ones_like(x)
self.assertEqual((out.numpy() == np.ones(shape, dtype)).all(), True)
out = paddle.tensor.ones_like(x)
self.assertEqual((out.numpy() == np.ones(shape, dtype)).all(), True)
out = paddle.tensor.creation.ones_like(x)
self.assertEqual((out.numpy() == np.ones(shape, dtype)).all(), True)
paddle.enable_static()
if __name__ == "__main__":
......
python/paddle/fluid/tests/unittests/test_ones_op.py
浏览文件 @ 2efcb481
......@@ -27,35 +27,35 @@ import numpy as np
class ApiOnesTest(unittest.TestCase):
def test_paddle_ones(self):
with paddle.program_guard(paddle.Program()):
with paddle.static.program_guard(paddle.static.Program()):
ones = paddle.ones(shape=[10])
place = paddle.CPUPlace()
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
result, = exe.run(fetch_list=[ones])
expected_result = np.ones(10, dtype="float32")
self.assertEqual((result == expected_result).all(), True)
with paddle.program_guard(paddle.Program()):
with paddle.static.program_guard(paddle.static.Program()):
ones = paddle.ones(shape=[10], dtype="float64")
place = paddle.CPUPlace()
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
result, = exe.run(fetch_list=[ones])
expected_result = np.ones(10, dtype="float64")
self.assertEqual((result == expected_result).all(), True)
with paddle.program_guard(paddle.Program()):
with paddle.static.program_guard(paddle.static.Program()):
ones = paddle.ones(shape=[10], dtype="int64")
place = paddle.CPUPlace()
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
result, = exe.run(fetch_list=[ones])
expected_result = np.ones(10, dtype="int64")
self.assertEqual((result == expected_result).all(), True)
def test_fluid_ones(self):
with paddle.program_guard(paddle.Program()):
with paddle.static.program_guard(paddle.static.Program()):
ones = fluid.layers.ones(shape=[10], dtype="int64")
place = paddle.CPUPlace()
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
result, = exe.run(fetch_list=[ones])
expected_result = np.ones(10, dtype="int64")
self.assertEqual((result == expected_result).all(), True)
......@@ -64,25 +64,25 @@ class ApiOnesTest(unittest.TestCase):
class ApiOnesZerosError(unittest.TestCase):
def test_errors(self):
def test_error1():
with paddle.program_guard(paddle.Program()):
with paddle.static.program_guard(paddle.static.Program()):
ones = paddle.ones(shape=10, dtype="int64")
self.assertRaises(TypeError, test_error1)
def test_error2():
with paddle.program_guard(paddle.Program()):
with paddle.static.program_guard(paddle.static.Program()):
ones = paddle.ones(shape=10)
self.assertRaises(TypeError, test_error2)
def test_error3():
with paddle.program_guard(paddle.Program()):
with paddle.static.program_guard(paddle.static.Program()):
ones = fluid.layers.ones(shape=10, dtype="int64")
self.assertRaises(TypeError, test_error3)
def test_error4():
with paddle.program_guard(paddle.Program()):
with paddle.static.program_guard(paddle.static.Program()):
ones = fluid.layers.ones(shape=[10], dtype="int8")
self.assertRaises(TypeError, test_error4)
......
python/paddle/fluid/tests/unittests/test_paddle_imperative_double_grad.py
浏览文件 @ 2efcb481
......@@ -22,7 +22,7 @@ import paddle
def _dygraph_guard_(func):
def __impl__(*args, **kwargs):
if paddle.in_imperative_mode():
if paddle.in_dynamic_mode():
return func(*args, **kwargs)
else:
with fluid.dygraph.guard():
......@@ -54,7 +54,7 @@ class TestDygraphDoubleGrad(TestCase):
allow_unused=False):
backward_strategy = fluid.dygraph.BackwardStrategy()
backward_strategy.sort_sum_gradient = self.sort_sum_gradient
return paddle.imperative.grad(
return paddle.grad(
outputs=outputs,
inputs=inputs,
grad_outputs=grad_outputs,
......
python/paddle/fluid/tests/unittests/test_randint_op.py
浏览文件 @ 2efcb481
......@@ -19,7 +19,7 @@ import numpy as np
from op_test import OpTest
import paddle
from paddle.fluid import core
from paddle import Program, program_guard
from paddle.static import program_guard, Program
def output_hist(out):
......@@ -132,7 +132,7 @@ class TestRandintAPI(unittest.TestCase):
place = paddle.CUDAPlace(0) if core.is_compiled_with_cuda(
) else paddle.CPUPlace()
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
outs = exe.run(
feed={'var_shape': np.array([100, 100]).astype('int64')},
fetch_list=[out1, out2, out3, out4, out5])
......@@ -141,13 +141,14 @@ class TestRandintAPI(unittest.TestCase):
class TestRandintImperative(unittest.TestCase):
def test_api(self):
n = 10
with paddle.imperative.guard():
x1 = paddle.randint(n, shape=[10], dtype="int32")
x2 = paddle.tensor.randint(n)
x3 = paddle.tensor.random.randint(n)
for i in [x1, x2, x3]:
for j in i.numpy().tolist():
self.assertTrue((j >= 0 and j < n))
paddle.disable_static()
x1 = paddle.randint(n, shape=[10], dtype="int32")
x2 = paddle.tensor.randint(n)
x3 = paddle.tensor.random.randint(n)
for i in [x1, x2, x3]:
for j in i.numpy().tolist():
self.assertTrue((j >= 0 and j < n))
paddle.enable_static()
if __name__ == "__main__":
......
python/paddle/fluid/tests/unittests/test_randn_op.py
浏览文件 @ 2efcb481
......@@ -18,7 +18,7 @@ import unittest
import numpy as np
import paddle
import paddle.fluid.core as core
from paddle import Program, program_guard
from paddle.static import program_guard, Program
class TestRandnOp(unittest.TestCase):
......@@ -39,7 +39,7 @@ class TestRandnOp(unittest.TestCase):
place = paddle.CUDAPlace(0) if core.is_compiled_with_cuda(
) else paddle.CPUPlace()
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
res = exe.run(train_program,
feed={'X': np.array(
shape, dtype='int32')},
......@@ -55,20 +55,21 @@ class TestRandnOpForDygraph(unittest.TestCase):
shape = [1000, 784]
place = paddle.CUDAPlace(0) if core.is_compiled_with_cuda(
) else paddle.CPUPlace()
with paddle.imperative.guard(place):
x1 = paddle.randn(shape, 'float32')
x2 = paddle.randn(shape, 'float64')
paddle.disable_static(place)
x1 = paddle.randn(shape, 'float32')
x2 = paddle.randn(shape, 'float64')
dim_1 = paddle.fill_constant([1], "int64", 20)
dim_2 = paddle.fill_constant([1], "int32", 50)
x3 = paddle.randn(shape=[dim_1, dim_2, 784])
dim_1 = paddle.fill_constant([1], "int64", 20)
dim_2 = paddle.fill_constant([1], "int32", 50)
x3 = paddle.randn(shape=[dim_1, dim_2, 784])
var_shape = paddle.imperative.to_variable(np.array(shape))
x4 = paddle.randn(var_shape)
var_shape = paddle.to_variable(np.array(shape))
x4 = paddle.randn(var_shape)
for out in [x1, x2, x3, x4]:
self.assertAlmostEqual(np.mean(out.numpy()), .0, delta=0.1)
self.assertAlmostEqual(np.std(out.numpy()), 1., delta=0.1)
for out in [x1, x2, x3, x4]:
self.assertAlmostEqual(np.mean(out.numpy()), .0, delta=0.1)
self.assertAlmostEqual(np.std(out.numpy()), 1., delta=0.1)
paddle.enable_static()
class TestRandnOpError(unittest.TestCase):
......
python/paddle/fluid/tests/unittests/test_randperm_op.py
浏览文件 @ 2efcb481
......@@ -17,7 +17,7 @@ import numpy as np
from op_test import OpTest
import paddle
import paddle.fluid.core as core
from paddle import Program, program_guard
from paddle.static import program_guard, Program
def check_randperm_out(n, data_np):
......@@ -108,7 +108,7 @@ class TestRandpermAPI(unittest.TestCase):
x1 = paddle.randperm(n)
x2 = paddle.randperm(n, 'float32')
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
res = exe.run(fetch_list=[x1, x2])
self.assertEqual(res[0].dtype, np.int64)
......@@ -119,13 +119,14 @@ class TestRandpermAPI(unittest.TestCase):
class TestRandpermImperative(unittest.TestCase):
def test_out(self):
with paddle.imperative.guard():
n = 10
for dtype in ['int32', np.int64, 'float32', 'float64']:
data_p = paddle.randperm(n, dtype)
data_np = data_p.numpy()
self.assertTrue(
check_randperm_out(n, data_np), msg=error_msg(data_np))
paddle.disable_static()
n = 10
for dtype in ['int32', np.int64, 'float32', 'float64']:
data_p = paddle.randperm(n, dtype)
data_np = data_p.numpy()
self.assertTrue(
check_randperm_out(n, data_np), msg=error_msg(data_np))
paddle.enable_static()
if __name__ == "__main__":
......
python/paddle/fluid/tests/unittests/test_retain_graph.py
浏览文件 @ 2efcb481
......@@ -17,7 +17,7 @@ import paddle
import paddle.fluid as fluid
import unittest
paddle.enable_imperative()
paddle.disable_static()
SEED = 2020
np.random.seed(SEED)
fluid.default_main_program().random_seed = SEED
......@@ -73,7 +73,7 @@ class TestRetainGraph(unittest.TestCase):
outs = paddle.fill_constant(disc_interpolates.shape,
disc_interpolates.dtype, 1.0)
gradients = paddle.imperative.grad(
gradients = paddle.grad(
outputs=disc_interpolates,
inputs=fake_AB,
grad_outputs=outs,
......@@ -103,8 +103,8 @@ class TestRetainGraph(unittest.TestCase):
A = np.random.rand(2, 3, 32, 32).astype('float32')
B = np.random.rand(2, 3, 32, 32).astype('float32')
realA = paddle.imperative.to_variable(A)
realB = paddle.imperative.to_variable(B)
realA = paddle.to_variable(A)
realB = paddle.to_variable(B)
fakeB = g(realA)
optim_d.clear_gradients()
......
python/paddle/fluid/tests/unittests/test_sort_op.py
浏览文件 @ 2efcb481
......@@ -17,7 +17,6 @@ from __future__ import print_function
import unittest
import paddle
import paddle.fluid as fluid
import paddle.imperative as imperative
import paddle.fluid.layers as layers
import numpy as np
import six
......@@ -72,16 +71,17 @@ class TestSortDygraph(unittest.TestCase):
self.place = core.CPUPlace()
def test_api_0(self):
with imperative.guard(self.place):
var_x = imperative.to_variable(self.input_data)
out = paddle.sort(var_x)
self.assertEqual((np.sort(self.input_data) == out.numpy()).all(),
True)
paddle.disable_static(self.place)
var_x = paddle.to_variable(self.input_data)
out = paddle.sort(var_x)
self.assertEqual((np.sort(self.input_data) == out.numpy()).all(), True)
paddle.enable_static()
def test_api_1(self):
with imperative.guard(self.place):
var_x = imperative.to_variable(self.input_data)
out = paddle.sort(var_x, axis=-1)
self.assertEqual(
(np.sort(
self.input_data, axis=-1) == out.numpy()).all(), True)
paddle.disable_static(self.place)
var_x = paddle.to_variable(self.input_data)
out = paddle.sort(var_x, axis=-1)
self.assertEqual(
(np.sort(
self.input_data, axis=-1) == out.numpy()).all(), True)
paddle.enable_static()
python/paddle/fluid/tests/unittests/test_zeros_like_op.py
浏览文件 @ 2efcb481
......@@ -62,20 +62,19 @@ class TestZerosLikeImpeartive(unittest.TestCase):
shape = [3, 4]
place = fluid.CUDAPlace(0) if core.is_compiled_with_cuda(
) else fluid.CPUPlace()
with paddle.imperative.guard(place):
x = paddle.imperative.to_variable(np.ones(shape))
for dtype in [np.bool, np.float32, np.float64, np.int32, np.int64]:
out = zeros_like(x, dtype)
self.assertEqual((out.numpy() == np.zeros(shape, dtype)).all(),
True)
out = paddle.tensor.zeros_like(x)
paddle.disable_static(place)
x = paddle.to_variable(np.ones(shape))
for dtype in [np.bool, np.float32, np.float64, np.int32, np.int64]:
out = zeros_like(x, dtype)
self.assertEqual((out.numpy() == np.zeros(shape, dtype)).all(),
True)
out = paddle.tensor.creation.zeros_like(x)
self.assertEqual((out.numpy() == np.zeros(shape, dtype)).all(),
True)
out = paddle.tensor.zeros_like(x)
self.assertEqual((out.numpy() == np.zeros(shape, dtype)).all(), True)
out = paddle.tensor.creation.zeros_like(x)
self.assertEqual((out.numpy() == np.zeros(shape, dtype)).all(), True)
paddle.enable_static()
if __name__ == "__main__":
......
python/paddle/fluid/tests/unittests/test_zeros_op.py
浏览文件 @ 2efcb481
......@@ -39,15 +39,15 @@ class ApiZerosTest(unittest.TestCase):
with program_guard(Program()):
zeros = paddle.zeros(shape=[10], dtype="float64")
place = paddle.CPUPlace()
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
result, = exe.run(fetch_list=[zeros])
expected_result = np.zeros(10, dtype="float64")
self.assertEqual((result == expected_result).all(), True)
with paddle.program_guard(Program()):
with paddle.static.program_guard(Program()):
zeros = paddle.zeros(shape=[10], dtype="int64")
place = paddle.CPUPlace()
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
result, = exe.run(fetch_list=[zeros])
expected_result = np.zeros(10, dtype="int64")
self.assertEqual((result == expected_result).all(), True)
......@@ -55,7 +55,7 @@ class ApiZerosTest(unittest.TestCase):
with program_guard(Program()):
zeros = paddle.zeros(shape=[10], dtype="int64")
place = paddle.CPUPlace()
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
result, = exe.run(fetch_list=[zeros])
expected_result = np.zeros(10, dtype="int64")
self.assertEqual((result == expected_result).all(), True)
......@@ -64,7 +64,7 @@ class ApiZerosTest(unittest.TestCase):
out_np = np.zeros(shape=(1), dtype='float32')
out = paddle.zeros(shape=[1], dtype="float32")
place = paddle.CPUPlace()
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
result = exe.run(fetch_list=[out])
self.assertEqual((result == out_np).all(), True)
......@@ -72,7 +72,7 @@ class ApiZerosTest(unittest.TestCase):
with program_guard(Program()):
zeros = fluid.layers.zeros(shape=[10], dtype="int64")
place = paddle.CPUPlace()
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
result, = exe.run(fetch_list=[zeros])
expected_result = np.zeros(10, dtype="int64")
self.assertEqual((result == expected_result).all(), True)
......@@ -81,13 +81,13 @@ class ApiZerosTest(unittest.TestCase):
class ApiZerosError(unittest.TestCase):
def test_errors(self):
def test_error1():
with paddle.program_guard(fluid.Program()):
with paddle.static.program_guard(fluid.Program()):
ones = fluid.layers.zeros(shape=10, dtype="int64")
self.assertRaises(TypeError, test_error1)
def test_error2():
with paddle.program_guard(fluid.Program()):
with paddle.static.program_guard(fluid.Program()):
ones = fluid.layers.zeros(shape=[10], dtype="int8")
self.assertRaises(TypeError, test_error2)
......
python/paddle/framework/__init__.py
浏览文件 @ 2efcb481
......@@ -14,23 +14,49 @@
# TODO: import framework api under this directory
__all__ = [
'append_backward', 'gradients', 'Executor', 'global_scope', 'scope_guard',
'BuildStrategy', 'CompiledProgram', 'default_main_program',
'default_startup_program', 'create_global_var', 'create_parameter', 'Print',
'py_func', 'ExecutionStrategy', 'name_scope', 'ParallelExecutor',
'ParamAttr', 'Program', 'program_guard', 'Variable', 'WeightNormParamAttr',
'create_global_var', 'create_parameter', 'ParamAttr', 'Variable',
'CPUPlace', 'CUDAPlace', 'CUDAPinnedPlace'
]
__all__ += [
'BackwardStrategy', 'grad', 'LayerList', 'load', 'save', 'prepare_context',
'to_variable', 'no_grad', 'ParallelEnv', 'DataParallel'
]
__all__ += [
'NoamDecay', 'PiecewiseDecay', 'NaturalExpDecay', 'ExponentialDecay',
'InverseTimeDecay', 'PolynomialDecay', 'CosineDecay'
]
from . import random
from .random import manual_seed
from ..fluid.executor import Executor, global_scope, scope_guard
from ..fluid.backward import append_backward, gradients
from ..fluid.compiler import BuildStrategy, CompiledProgram, ExecutionStrategy
from ..fluid.framework import default_main_program, default_startup_program, name_scope, Program, program_guard, Variable
from ..fluid.layers.control_flow import Print
from ..fluid.layers.nn import py_func
from ..fluid.parallel_executor import ParallelExecutor
from ..fluid.param_attr import ParamAttr, WeightNormParamAttr
from ..fluid.layers.tensor import create_global_var, create_parameter
from ..fluid.core import CPUPlace, CUDAPlace, CUDAPinnedPlace
from ..fluid.framework import Variable #DEFINE_ALIAS
from ..fluid.param_attr import ParamAttr #DEFINE_ALIAS
from ..fluid.layers.tensor import create_global_var #DEFINE_ALIAS
from ..fluid.layers.tensor import create_parameter #DEFINE_ALIAS
from ..fluid.core import CPUPlace #DEFINE_ALIAS
from ..fluid.core import CUDAPlace #DEFINE_ALIAS
from ..fluid.core import CUDAPinnedPlace #DEFINE_ALIAS
from paddle.fluid import core #DEFINE_ALIAS
from ..fluid.dygraph.base import no_grad #DEFINE_ALIAS
from ..fluid.dygraph.base import to_variable #DEFINE_ALIAS
from ..fluid.dygraph.base import grad #DEFINE_ALIAS
from ..fluid.dygraph.checkpoint import load_dygraph #DEFINE_ALIAS
from ..fluid.dygraph.checkpoint import save_dygraph #DEFINE_ALIAS
from ..fluid.dygraph.checkpoint import load_dygraph as load #DEFINE_ALIAS
from ..fluid.dygraph.checkpoint import save_dygraph as save #DEFINE_ALIAS
from ..fluid.dygraph.parallel import prepare_context #DEFINE_ALIAS
from ..fluid.dygraph.parallel import ParallelEnv #DEFINE_ALIAS
from ..fluid.dygraph.parallel import DataParallel #DEFINE_ALIAS
from ..fluid.dygraph.learning_rate_scheduler import NoamDecay #DEFINE_ALIAS
from ..fluid.dygraph.learning_rate_scheduler import PiecewiseDecay #DEFINE_ALIAS
from ..fluid.dygraph.learning_rate_scheduler import NaturalExpDecay #DEFINE_ALIAS
from ..fluid.dygraph.learning_rate_scheduler import ExponentialDecay #DEFINE_ALIAS
from ..fluid.dygraph.learning_rate_scheduler import InverseTimeDecay #DEFINE_ALIAS
from ..fluid.dygraph.learning_rate_scheduler import PolynomialDecay #DEFINE_ALIAS
from ..fluid.dygraph.learning_rate_scheduler import CosineDecay #DEFINE_ALIAS
BackwardStrategy = core.BackwardStrategy
python/paddle/imperative/__init__.py 已删除 100644 → 0
浏览文件 @ cd7b55a2
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# define api used to run in imperative mode
__all__ = [
'BackwardStrategy', 'enabled', 'grad', 'guard', 'LayerList', 'load', 'save',
'prepare_context', 'to_variable', 'TracedLayer', 'no_grad', 'ParallelEnv',
'ProgramTranslator', 'declarative', 'DataParallel', 'TranslatedLayer', 'jit'
]
__all__ += [
'NoamDecay', 'PiecewiseDecay', 'NaturalExpDecay', 'ExponentialDecay',
'InverseTimeDecay', 'PolynomialDecay', 'CosineDecay'
]
from paddle.fluid import core
from ..fluid.dygraph.base import enabled, guard, no_grad, to_variable, grad
from ..fluid.dygraph.checkpoint import load_dygraph as load
from ..fluid.dygraph.checkpoint import save_dygraph as save
from ..fluid.dygraph.parallel import prepare_context, ParallelEnv, DataParallel
from ..fluid.dygraph.jit import TracedLayer, declarative
from ..fluid.dygraph import ProgramTranslator
from . import jit
from ..fluid.dygraph.learning_rate_scheduler import NoamDecay, PiecewiseDecay, NaturalExpDecay, ExponentialDecay, \
InverseTimeDecay, PolynomialDecay, CosineDecay
BackwardStrategy = core.BackwardStrategy
python/paddle/incubate/complex/tensor/math.py
浏览文件 @ 2efcb481
......@@ -261,8 +261,8 @@ def trace(x, offset=0, axis1=0, axis2=1, name=None):
case1 = np.random.randn(3, 10, 10).astype('float64') + 1j * np.random.randn(3, 10, 10).astype('float64')
paddle.enable_imperative()
case1 = paddle.imperative.to_variable(case1)
paddle.disable_static()
case1 = paddle.to_variable(case1)
data1 = paddle.complex.trace(case1, offset=1, axis1=1, axis2=2) # data1.shape = [3]
"""
complex_variable_exists([x], "trace")
......
python/paddle/incubate/hapi/text/text.py
浏览文件 @ 2efcb481
......@@ -1804,7 +1804,7 @@ class DynamicDecode(Layer):
from paddle.fluid.layers import BeamSearchDecoder
from paddle.incubate.hapi.text import StackedLSTMCell, DynamicDecode
paddle.enable_dygraph()
paddle.disable_static()
vocab_size, d_model, = 100, 32
encoder_output = paddle.rand((2, 4, d_model))
......@@ -2278,7 +2278,7 @@ class TransformerCell(RNNCell):
from paddle.incubate.hapi.text import TransformerBeamSearchDecoder
from paddle.incubate.hapi.text import DynamicDecode
paddle.enable_dygraph()
paddle.disable_static()
class Embedder(fluid.dygraph.Layer):
def __init__(self):
......@@ -2445,7 +2445,7 @@ class TransformerBeamSearchDecoder(layers.BeamSearchDecoder):
from paddle.incubate.hapi.text import TransformerBeamSearchDecoder
from paddle.incubate.hapi.text import DynamicDecode
paddle.enable_dygraph()
paddle.disable_static()
class Embedder(fluid.dygraph.Layer):
def __init__(self):
......
python/paddle/imperative/jit/__init__.py → python/paddle/jit/__init__.py
浏览文件 @ 2efcb481
......@@ -12,7 +12,16 @@
# See the License for the specific language governing permissions and
# limitations under the License.
from ...fluid.dygraph.jit import save, load, SaveLoadConfig
from ...fluid.dygraph.io import TranslatedLayer
from ..fluid.dygraph.jit import save #DEFINE_ALIAS
from ..fluid.dygraph.jit import load #DEFINE_ALIAS
from ..fluid.dygraph.jit import SaveLoadConfig #DEFINE_ALIAS
from ..fluid.dygraph.jit import TracedLayer #DEFINE_ALIAS
from ..fluid.dygraph.jit import declarative as __impl__ #DEFINE_ALIAS
from ..fluid.dygraph.jit import declarative as to_static #DEFINE_ALIAS
from ..fluid.dygraph import ProgramTranslator #DEFINE_ALIAS
from ..fluid.dygraph.io import TranslatedLayer #DEFINE_ALIAS
__all__ = ['save', 'load', 'SaveLoadConfig']
__all__ = [
'save', 'load', 'SaveLoadConfig', 'TracedLayer', 'to_static',
'ProgramTranslator', 'TranslatedLayer'
]
python/paddle/static/__init__.py 0 → 100644
浏览文件 @ 2efcb481
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# TODO: import framework api under this directory
__all__ = [
'append_backward', 'gradients', 'Executor', 'global_scope', 'scope_guard',
'BuildStrategy', 'CompiledProgram', 'Print', 'py_func', 'ExecutionStrategy',
'name_scope', 'ParallelExecutor', 'program_guard', 'WeightNormParamAttr',
'default_main_program', 'default_startup_program', 'Program', 'save', 'load'
]
from ..fluid.executor import Executor #DEFINE_ALIAS
from ..fluid.executor import global_scope #DEFINE_ALIAS
from ..fluid.executor import scope_guard #DEFINE_ALIAS
from ..fluid.backward import append_backward #DEFINE_ALIAS
from ..fluid.backward import gradients #DEFINE_ALIAS
from ..fluid.compiler import BuildStrategy #DEFINE_ALIAS
from ..fluid.compiler import CompiledProgram #DEFINE_ALIAS
from ..fluid.compiler import ExecutionStrategy #DEFINE_ALIAS
from ..fluid.framework import default_main_program #DEFINE_ALIAS
from ..fluid.framework import default_startup_program #DEFINE_ALIAS
from ..fluid.framework import Program #DEFINE_ALIAS
from ..fluid.framework import name_scope #DEFINE_ALIAS
from ..fluid.framework import program_guard #DEFINE_ALIAS
from ..fluid.layers.control_flow import Print #DEFINE_ALIAS
from ..fluid.layers.nn import py_func #DEFINE_ALIAS
from ..fluid.parallel_executor import ParallelExecutor #DEFINE_ALIAS
from ..fluid.param_attr import WeightNormParamAttr #DEFINE_ALIAS
from ..tensor.io import save #DEFINE_ALIAS
from ..tensor.io import load #DEFINE_ALIAS
python/paddle/declarative/__init__.py → python/paddle/static/nn/__init__.py
浏览文件 @ 2efcb481
......@@ -16,29 +16,45 @@ __all__ = [
'fc',
'batch_norm',
'embedding',
'bilinear_tensor_product'
'conv2d'
'conv2d_transpose'
'conv3d'
'conv3d_transpose'
'create_parameter'
'crf_decoding'
'data_norm'
'deformable_conv'
'group_norm'
'hsigmoid'
'instance_norm'
'layer_norm'
'multi_box_head'
'nce'
'prelu'
'row_conv'
'bilinear_tensor_product',
'conv2d',
'conv2d_transpose',
'conv3d',
'conv3d_transpose',
'create_parameter',
'crf_decoding',
'data_norm',
'deformable_conv',
'group_norm',
'hsigmoid',
'instance_norm',
'layer_norm',
'multi_box_head',
'nce',
'prelu',
'row_conv',
'spectral_norm',
]
from ..fluid.layers import fc, batch_norm, bilinear_tensor_product, \
conv2d, conv2d_transpose, conv3d, conv3d_transpose, create_parameter, \
crf_decoding, data_norm, deformable_conv, group_norm, hsigmoid, instance_norm, \
layer_norm, multi_box_head, nce, prelu, row_conv, spectral_norm
from ...fluid.layers import fc #DEFINE_ALIAS
from ...fluid.layers import batch_norm #DEFINE_ALIAS
from ...fluid.layers import bilinear_tensor_product #DEFINE_ALIAS
from ...fluid.layers import conv2d #DEFINE_ALIAS
from ...fluid.layers import conv2d_transpose #DEFINE_ALIAS
from ...fluid.layers import conv3d #DEFINE_ALIAS
from ...fluid.layers import conv3d_transpose #DEFINE_ALIAS
from ...fluid.layers import create_parameter #DEFINE_ALIAS
from ...fluid.layers import crf_decoding #DEFINE_ALIAS
from ...fluid.layers import data_norm #DEFINE_ALIAS
from ...fluid.layers import deformable_conv #DEFINE_ALIAS
from ...fluid.layers import group_norm #DEFINE_ALIAS
from ...fluid.layers import hsigmoid #DEFINE_ALIAS
from ...fluid.layers import instance_norm #DEFINE_ALIAS
from ...fluid.layers import layer_norm #DEFINE_ALIAS
from ...fluid.layers import multi_box_head #DEFINE_ALIAS
from ...fluid.layers import nce #DEFINE_ALIAS
from ...fluid.layers import prelu #DEFINE_ALIAS
from ...fluid.layers import row_conv #DEFINE_ALIAS
from ...fluid.layers import spectral_norm #DEFINE_ALIAS
from ..fluid.input import embedding
from ...fluid.input import embedding #DEFINE_ALIAS
python/paddle/tensor/creation.py
浏览文件 @ 2efcb481
......@@ -83,7 +83,7 @@ def full_like(x, fill_value, dtype=None, name=None):
import paddle
import numpy as np
paddle.enable_imperative() # Now we are in imperative mode
paddle.disable_static() # Now we are in imperative mode
input = paddle.full(shape=[2, 3], fill_value=0.0, dtype='float32', name='input')
output = paddle.full_like(input, 2.0)
# [[2. 2. 2.]
......@@ -143,7 +143,7 @@ def ones(shape, dtype=None, name=None):
.. code-block:: python
import paddle
paddle.enable_imperative()
paddle.disable_static()
# default dtype for ones OP
data1 = paddle.ones(shape=[3, 2])
......@@ -199,9 +199,9 @@ def ones_like(x, dtype=None, name=None):
import paddle
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
x = paddle.imperative.to_variable(np.array([1,2,3], dtype='float32'))
x = paddle.to_variable(np.array([1,2,3], dtype='float32'))
out1 = paddle.zeros_like(x) # [1., 1., 1.]
out2 = paddle.zeros_like(x, dtype='int32') # [1, 1, 1]
......@@ -236,7 +236,7 @@ def zeros(shape, dtype=None, name=None):
import paddle
paddle.enable_imperative() # Now we are in imperative mode
paddle.disable_static() # Now we are in imperative mode
data = paddle.zeros(shape=[3, 2], dtype='float32')
# [[0. 0.]
# [0. 0.]
......@@ -289,9 +289,9 @@ def zeros_like(x, dtype=None, name=None):
import paddle
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
x = paddle.imperative.to_variable(np.array([1,2,3], dtype='float32'))
x = paddle.to_variable(np.array([1,2,3], dtype='float32'))
out1 = paddle.zeros_like(x) # [0., 0., 0.]
out2 = paddle.zeros_like(x, dtype='int32') # [0, 0, 0]
......@@ -328,7 +328,7 @@ def eye(num_rows, num_columns=None, dtype=None, name=None):
import paddle
paddle.enable_imperative() # Now we are in imperative mode
paddle.disable_static() # Now we are in imperative mode
data = paddle.eye(3, dtype='int32')
# [[1 0 0]
# [0 1 0]
......@@ -382,7 +382,7 @@ def full(shape, fill_value, dtype=None, name=None):
import paddle
paddle.enable_imperative() # Now we are in imperative mode
paddle.disable_static() # Now we are in imperative mode
data1 = paddle.full(shape=[2,1], fill_value=0, dtype='int64')
#[[0]
# [0]]
......@@ -459,7 +459,7 @@ def arange(start=0, end=None, step=1, dtype=None, name=None):
import paddle
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
out1 = paddle.arange(5)
# [0, 1, 2, 3, 4]
......@@ -471,7 +471,7 @@ def arange(start=0, end=None, step=1, dtype=None, name=None):
out3 = paddle.arange(4.999, dtype='float32')
# [0., 1., 2., 3., 4.]
start_var = paddle.imperative.to_variable(np.array([3]))
start_var = paddle.to_variable(np.array([3]))
out4 = paddle.arange(start_var, 7)
# [3, 4, 5, 6]
......@@ -709,12 +709,12 @@ def meshgrid(*args, **kwargs):
import paddle
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
input_3 = np.random.randint(0, 100, [100, ]).astype('int32')
input_4 = np.random.randint(0, 100, [200, ]).astype('int32')
tensor_3 = paddle.imperative.to_variable(input_3)
tensor_4 = paddle.imperative.to_variable(input_4)
tensor_3 = paddle.to_variable(input_3)
tensor_4 = paddle.to_variable(input_4)
grid_x, grid_y = paddle.tensor.meshgrid(tensor_3, tensor_4)
#the shape of grid_x is (100, 200)
......
python/paddle/tensor/linalg.py
浏览文件 @ 2efcb481
......@@ -605,10 +605,10 @@ def cross(x, y, axis=None, name=None):
Examples:
.. code-block:: python
import paddle
from paddle.imperative import to_variable
from paddle import to_variable
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
data_x = np.array([[1.0, 1.0, 1.0],
[2.0, 2.0, 2.0],
......@@ -782,13 +782,13 @@ def histogram(input, bins=100, min=0, max=0):
.. code-block:: python
import paddle
import numpy as np
startup_program = paddle.Program()
train_program = paddle.Program()
with paddle.program_guard(train_program, startup_program):
startup_program = paddle.static.Program()
train_program = paddle.static.Program()
with paddle.static.program_guard(train_program, startup_program):
inputs = paddle.data(name='input', dtype='int32', shape=[2,3])
output = paddle.histogram(inputs, bins=5, min=1, max=5)
place = paddle.CPUPlace()
exe = paddle.Executor(place)
exe = paddle.static.Executor(place)
exe.run(startup_program)
img = np.array([[2, 4, 2], [2, 5, 4]]).astype(np.int32)
res = exe.run(train_program,
......@@ -800,11 +800,12 @@ def histogram(input, bins=100, min=0, max=0):
.. code-block:: python
import paddle
import numpy as np
with paddle.imperative.guard(paddle.CPUPlace()):
inputs_np = np.array([1, 2, 1]).astype(np.float)
inputs = paddle.imperative.to_variable(inputs_np)
result = paddle.histogram(inputs, bins=4, min=0, max=3)
print(result) # [0, 2, 1, 0]
paddle.disable_static(paddle.CPUPlace())
inputs_np = np.array([1, 2, 1]).astype(np.float)
inputs = paddle.to_variable(inputs_np)
result = paddle.histogram(inputs, bins=4, min=0, max=3)
print(result) # [0, 2, 1, 0]
paddle.enable_static()
"""
if in_dygraph_mode():
return core.ops.histogram(input, "bins", bins, "min", min, "max", max)
......
python/paddle/tensor/logic.py
浏览文件 @ 2efcb481
......@@ -71,12 +71,11 @@ def equal_all(x, y, name=None):
import numpy as np
import paddle
import paddle.imperative as imperative
paddle.enable_imperative()
x = imperative.to_variable(np.array([1, 2, 3]))
y = imperative.to_variable(np.array([1, 2, 3]))
z = imperative.to_variable(np.array([1, 4, 3]))
paddle.disable_static()
x = paddle.to_variable(np.array([1, 2, 3]))
y = paddle.to_variable(np.array([1, 2, 3]))
z = paddle.to_variable(np.array([1, 4, 3]))
result1 = paddle.equal_all(x, y)
print(result1.numpy()) # result1 = [True ]
result2 = paddle.equal_all(x, z)
......@@ -201,11 +200,10 @@ def equal(x, y, name=None):
import numpy as np
import paddle
import paddle.imperative as imperative
paddle.enable_imperative()
x = imperative.to_variable(np.array([1, 2, 3]))
y = imperative.to_variable(np.array([1, 3, 2]))
paddle.disable_static()
x = paddle.to_variable(np.array([1, 2, 3]))
y = paddle.to_variable(np.array([1, 3, 2]))
result1 = paddle.equal(x, y)
print(result1.numpy()) # result1 = [True False False]
"""
......@@ -234,11 +232,10 @@ def greater_equal(x, y, name=None):
.. code-block:: python
import numpy as np
import paddle
import paddle.imperative as imperative
paddle.enable_imperative()
x = imperative.to_variable(np.array([1, 2, 3]))
y = imperative.to_variable(np.array([1, 3, 2]))
paddle.disable_static()
x = paddle.to_variable(np.array([1, 2, 3]))
y = paddle.to_variable(np.array([1, 3, 2]))
result1 = paddle.greater_equal(x, y)
print(result1.numpy()) # result1 = [True False True]
"""
......@@ -267,11 +264,10 @@ def greater_than(x, y, name=None):
.. code-block:: python
import numpy as np
import paddle
import paddle.imperative as imperative
paddle.enable_imperative()
x = imperative.to_variable(np.array([1, 2, 3]))
y = imperative.to_variable(np.array([1, 3, 2]))
paddle.disable_static()
x = paddle.to_variable(np.array([1, 2, 3]))
y = paddle.to_variable(np.array([1, 3, 2]))
result1 = paddle.greater_than(x, y)
print(result1.numpy()) # result1 = [False False True]
"""
......@@ -301,11 +297,10 @@ def less_equal(x, y, name=None):
.. code-block:: python
import numpy as np
import paddle
import paddle.imperative as imperative
paddle.enable_imperative()
x = imperative.to_variable(np.array([1, 2, 3]))
y = imperative.to_variable(np.array([1, 3, 2]))
paddle.disable_static()
x = paddle.to_variable(np.array([1, 2, 3]))
y = paddle.to_variable(np.array([1, 3, 2]))
result1 = paddle.less_equal(x, y)
print(result1.numpy()) # result1 = [True True False]
"""
......@@ -335,11 +330,10 @@ def less_than(x, y, name=None):
.. code-block:: python
import numpy as np
import paddle
import paddle.imperative as imperative
paddle.enable_imperative()
x = imperative.to_variable(np.array([1, 2, 3]))
y = imperative.to_variable(np.array([1, 3, 2]))
paddle.disable_static()
x = paddle.to_variable(np.array([1, 2, 3]))
y = paddle.to_variable(np.array([1, 3, 2]))
result1 = paddle.less_than(x, y)
print(result1.numpy()) # result1 = [False True False]
"""
......@@ -369,11 +363,10 @@ def not_equal(x, y, name=None):
.. code-block:: python
import numpy as np
import paddle
import paddle.imperative as imperative
paddle.enable_imperative()
x = imperative.to_variable(np.array([1, 2, 3]))
y = imperative.to_variable(np.array([1, 3, 2]))
paddle.disable_static()
x = paddle.to_variable(np.array([1, 2, 3]))
y = paddle.to_variable(np.array([1, 3, 2]))
result1 = paddle.not_equal(x, y)
print(result1.numpy()) # result1 = [False True True]
"""
......
python/paddle/tensor/manipulation.py
浏览文件 @ 2efcb481
......@@ -103,16 +103,16 @@ def concat(x, axis=0, name=None):
import paddle
import numpy as np
paddle.enable_imperative() # Now we are in imperative mode
paddle.disable_static() # Now we are in imperative mode
in1 = np.array([[1, 2, 3],
[4, 5, 6]])
in2 = np.array([[11, 12, 13],
[14, 15, 16]])
in3 = np.array([[21, 22],
[23, 24]])
x1 = paddle.imperative.to_variable(in1)
x2 = paddle.imperative.to_variable(in2)
x3 = paddle.imperative.to_variable(in3)
x1 = paddle.to_variable(in1)
x2 = paddle.to_variable(in2)
x3 = paddle.to_variable(in3)
zero = paddle.full(shape=[1], dtype='int32', fill_value=0)
# When the axis is negative, the real axis is (axis + Rank(x))
# As follow, axis is -1, Rank(x) is 2, the real axis is 1
......@@ -156,12 +156,12 @@ def flip(x, axis, name=None):
import paddle
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
image_shape=(3, 2, 2)
x = np.arange(image_shape[0] * image_shape[1] * image_shape[2]).reshape(image_shape)
x = x.astype('float32')
img = paddle.imperative.to_variable(x)
img = paddle.to_variable(x)
out = paddle.flip(img, [0,1])
print(out) # [[[10,11][8, 9]],[[6, 7],[4, 5]] [[2, 3],[0, 1]]]
......@@ -247,13 +247,13 @@ def flatten(x, start_axis=0, stop_axis=-1, name=None):
import paddle
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
image_shape=(2, 3, 4, 4)
x = np.arange(image_shape[0] * image_shape[1] * image_shape[2] * image_shape[3]).reshape(image_shape) / 100.
x = x.astype('float32')
img = paddle.imperative.to_variable(x)
img = paddle.to_variable(x)
out = paddle.flatten(img, start_axis=1, stop_axis=2)
# out shape is [2, 12, 4]
"""
......@@ -325,8 +325,8 @@ def roll(x, shifts, axis=None, name=None):
data = np.array([[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]])
paddle.enable_imperative()
x = paddle.imperative.to_variable(data)
paddle.disable_static()
x = paddle.to_variable(data)
out_z1 = paddle.roll(x, shifts=1)
print(out_z1.numpy())
#[[9. 1. 2.]
......@@ -503,10 +503,10 @@ def split(x, num_or_sections, axis=0, name=None):
import numpy as np
import paddle
paddle.enable_imperative()
paddle.disable_static()
# x is a Tensor which shape is [3, 9, 5]
x_np = np.random.random([3, 9, 5]).astype("int32")
x = paddle.imperative.to_variable(x_np)
x = paddle.to_variable(x_np)
out0, out1, out22 = paddle.split(x, num_or_sections=3, axis=1)
# out0.shape [3, 3, 5]
......@@ -595,7 +595,7 @@ def squeeze(x, axis=None, name=None):
import paddle
paddle.enable_imperative()
paddle.disable_static()
x = paddle.rand([5, 1, 10])
output = paddle.squeeze(x, axis=1)
......
python/paddle/tensor/math.py
浏览文件 @ 2efcb481
......@@ -487,18 +487,18 @@ Examples:
import paddle
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
x_data = np.array([[1, 2], [3, 4]], dtype=np.float32)
y_data = np.array([[5, 6], [7, 8]], dtype=np.float32)
x = paddle.imperative.to_variable(x_data)
y = paddle.imperative.to_variable(y_data)
x = paddle.to_variable(x_data)
y = paddle.to_variable(y_data)
res = paddle.multiply(x, y)
print(res.numpy()) # [[5, 12], [21, 32]]
x_data = np.array([[[1, 2, 3], [1, 2, 3]]], dtype=np.float32)
y_data = np.array([1, 2], dtype=np.float32)
x = paddle.imperative.to_variable(x_data)
y = paddle.imperative.to_variable(y_data)
x = paddle.to_variable(x_data)
y = paddle.to_variable(y_data)
res = paddle.multiply(x, y, axis=1)
print(res.numpy()) # [[[1, 2, 3], [2, 4, 6]]]
......@@ -1431,11 +1431,11 @@ def trace(x, offset=0, axis1=0, axis2=1, name=None):
case2 = np.random.randn(3, 10, 10).astype('float32')
case3 = np.random.randn(3, 10, 5, 10).astype('float32')
paddle.enable_imperative()
paddle.disable_static()
case1 = paddle.imperative.to_variable(case1)
case2 = paddle.imperative.to_variable(case2)
case3 = paddle.imperative.to_variable(case3)
case1 = paddle.to_variable(case1)
case2 = paddle.to_variable(case2)
case3 = paddle.to_variable(case3)
data1 = paddle.trace(case1) # data1.shape = [1]
data2 = paddle.trace(case2, offset=1, axis1=1, axis2=2) # data2.shape = [3]
data3 = paddle.trace(case3, offset=-3, axis1=1, axis2=-1) # data2.shape = [3, 5]
......
python/paddle/tensor/random.py
浏览文件 @ 2efcb481
......@@ -81,7 +81,7 @@ def randint(low=0, high=None, shape=[1], dtype=None, name=None):
import paddle
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
# example 1:
# attr shape is a list which doesn't contain Tensor.
......@@ -98,7 +98,7 @@ def randint(low=0, high=None, shape=[1], dtype=None, name=None):
# example 3:
# attr shape is a Tensor
var_shape = paddle.imperative.to_variable(np.array([3]))
var_shape = paddle.to_variable(np.array([3]))
result_3 = paddle.randint(low=-5, high=5, shape=var_shape)
# [-2, 2, 3]
......@@ -187,7 +187,7 @@ def randn(shape, dtype=None, name=None):
import paddle
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
# example 1: attr shape is a list which doesn't contain Tensor.
result_1 = paddle.randn(shape=[2, 3])
......@@ -206,7 +206,7 @@ def randn(shape, dtype=None, name=None):
# [ 0.8086993 , 0.6868893 ]]]
# example 3: attr shape is a Tensor, the data type must be int64 or int32.
var_shape = paddle.imperative.to_variable(np.array([2, 3]))
var_shape = paddle.to_variable(np.array([2, 3]))
result_3 = paddle.randn(var_shape)
# [[-2.878077 , 0.17099959, 0.05111201]
# [-0.3761474, -1.044801 , 1.1870178 ]]
......@@ -252,7 +252,7 @@ def randperm(n, dtype="int64", name=None):
import paddle
paddle.enable_imperative()
paddle.disable_static()
result_1 = paddle.randperm(5)
# [4, 1, 2, 3, 0]
......@@ -325,7 +325,7 @@ def rand(shape, dtype=None, name=None):
import paddle
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
# example 1: attr shape is a list which doesn't contain Tensor.
result_1 = paddle.rand(shape=[2, 3])
# [[0.451152 , 0.55825245, 0.403311 ],
......@@ -343,7 +343,7 @@ def rand(shape, dtype=None, name=None):
# [0.870881 , 0.2984597 ]]]
# example 3: attr shape is a Tensor, the data type must be int64 or int32.
var_shape = paddle.imperative.to_variable(np.array([2, 3]))
var_shape = paddle.to_variable(np.array([2, 3]))
result_3 = paddle.rand(var_shape)
# [[0.22920267, 0.841956 , 0.05981819],
# [0.4836288 , 0.24573246, 0.7516129 ]]
......
python/paddle/tensor/search.py
浏览文件 @ 2efcb481
......@@ -68,17 +68,16 @@ def argsort(x, axis=-1, descending=False, name=None):
Examples:
.. code-block:: python
import paddle
import paddle.imperative as imperative
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
input_array = np.array([[[5,8,9,5],
[0,0,1,7],
[6,9,2,4]],
[[5,2,4,2],
[4,7,7,9],
[1,7,0,6]]]).astype(np.float32)
x = imperative.to_variable(input_array)
x = paddle.to_variable(input_array)
out1 = paddle.argsort(x=x, axis=-1)
out2 = paddle.argsort(x=x, axis=0)
out3 = paddle.argsort(x=x, axis=1)
......@@ -250,14 +249,14 @@ def index_select(x, index, axis=0, name=None):
import paddle
import numpy as np
paddle.enable_imperative() # Now we are in imperative mode
paddle.disable_static() # Now we are in imperative mode
data = np.array([[1.0, 2.0, 3.0, 4.0],
[5.0, 6.0, 7.0, 8.0],
[9.0, 10.0, 11.0, 12.0]])
data_index = np.array([0, 1, 1]).astype('int32')
x = paddle.imperative.to_variable(data)
index = paddle.imperative.to_variable(data_index)
x = paddle.to_variable(data)
index = paddle.to_variable(data_index)
out_z1 = paddle.index_select(x=x, index=index)
#[[1. 2. 3. 4.]
# [5. 6. 7. 8.]
......@@ -399,17 +398,16 @@ def sort(x, axis=-1, descending=False, name=None):
Examples:
.. code-block:: python
import paddle
import paddle.imperative as imperative
import numpy as np
paddle.enable_imperative()
paddle.disable_static()
input_array = np.array([[[5,8,9,5],
[0,0,1,7],
[6,9,2,4]],
[[5,2,4,2],
[4,7,7,9],
[1,7,0,6]]]).astype(np.float32)
x = imperative.to_variable(input_array)
x = paddle.to_variable(input_array)
out1 = paddle.sort(x=x, axis=-1)
out2 = paddle.sort(x=x, axis=0)
out3 = paddle.sort(x=x, axis=1)
......
python/setup.py.in
浏览文件 @ 2efcb481
......@@ -154,6 +154,7 @@ packages=['paddle',
'paddle.fleet.proto',
'paddle.fleet.utils',
'paddle.framework',
'paddle.jit',
'paddle.fluid',
'paddle.fluid.dygraph',
'paddle.fluid.dygraph.dygraph_to_static',
......@@ -200,8 +201,8 @@ packages=['paddle',
'paddle.nn.layer',
'paddle.nn.initializer',
'paddle.metric',
'paddle.imperative',
'paddle.imperative.jit',
'paddle.static',
'paddle.static.nn',
'paddle.tensor',
]
......
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