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未验证 提交 4d3b7d7d 编写于 作者: W Weilong Wu 提交者： GitHub
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[Eager] FLAGS_retain_grad_for_all_tensor set false in default (#43142) 

* [Eager] FLAGS_retain_grad set false

* Add FLAGS_retain_grad_ for some tests

* Add FLAGS_retain_grad_ to some tests

* modified set_flags

* modified set_flags

* fix windows-ci and windows-openblas-ci

* import paddle.fluid
上级 1e0ea6a4
隐藏空白更改
内联 并排
Showing with 134 addition and 1 deletion
paddle/fluid/eager/utils.cc
浏览文件 @ 4d3b7d7d
...@@ -27,7 +27,7 @@ ...@@ -27,7 +27,7 @@
#include "paddle/fluid/framework/phi_utils.h" #include "paddle/fluid/framework/phi_utils.h"
#include "paddle/fluid/framework/variable.h" #include "paddle/fluid/framework/variable.h"
PADDLE_DEFINE_EXPORTED_bool(retain_grad_for_all_tensor, true, PADDLE_DEFINE_EXPORTED_bool(retain_grad_for_all_tensor, false,
"retain grad for all tensor"); "retain grad for all tensor");
namespace egr { namespace egr {
......
python/paddle/fluid/tests/custom_op/test_custom_tanh_double_grad.py
浏览文件 @ 4d3b7d7d
...@@ -17,6 +17,7 @@ import unittest ...@@ -17,6 +17,7 @@ import unittest
import numpy as np import numpy as np
import paddle import paddle
import paddle.fluid as fluid
import paddle.static as static import paddle.static as static
from paddle.utils.cpp_extension import load, get_build_directory from paddle.utils.cpp_extension import load, get_build_directory
from paddle.utils.cpp_extension.extension_utils import run_cmd from paddle.utils.cpp_extension.extension_utils import run_cmd
...@@ -40,6 +41,7 @@ custom_ops = load( ...@@ -40,6 +41,7 @@ custom_ops = load(
def custom_tanh_double_grad_dynamic(func, device, dtype, np_x): def custom_tanh_double_grad_dynamic(func, device, dtype, np_x):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
paddle.set_device(device) paddle.set_device(device)
t = paddle.to_tensor(np_x, dtype=dtype, stop_gradient=False) t = paddle.to_tensor(np_x, dtype=dtype, stop_gradient=False)
...@@ -55,6 +57,7 @@ def custom_tanh_double_grad_dynamic(func, device, dtype, np_x): ...@@ -55,6 +57,7 @@ def custom_tanh_double_grad_dynamic(func, device, dtype, np_x):
assert out.grad is not None assert out.grad is not None
assert dx[0].grad is not None assert dx[0].grad is not None
return dx[0].numpy(), dx[0].grad.numpy(), out.grad.numpy() return dx[0].numpy(), dx[0].grad.numpy(), out.grad.numpy()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
class TestCustomTanhDoubleGradJit(unittest.TestCase): class TestCustomTanhDoubleGradJit(unittest.TestCase):
...@@ -85,9 +88,11 @@ class TestCustomTanhDoubleGradJit(unittest.TestCase): ...@@ -85,9 +88,11 @@ class TestCustomTanhDoubleGradJit(unittest.TestCase):
dout, pd_dout)) dout, pd_dout))
def test_func_double_grad_dynamic(self): def test_func_double_grad_dynamic(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_double_grad_dynamic() self.func_double_grad_dynamic()
self.func_double_grad_dynamic() self.func_double_grad_dynamic()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
if __name__ == "__main__": if __name__ == "__main__":
......
python/paddle/fluid/tests/unittests/autograd/test_autograd_functional_dynamic.py
浏览文件 @ 4d3b7d7d
...@@ -18,6 +18,7 @@ import unittest ...@@ -18,6 +18,7 @@ import unittest
import numpy as np import numpy as np
import paddle import paddle
import paddle.fluid as fluid
import paddle.compat as cpt import paddle.compat as cpt
import paddle.nn.functional as F import paddle.nn.functional as F
from paddle.autograd.functional import _as_tensors from paddle.autograd.functional import _as_tensors
...@@ -490,6 +491,8 @@ class TestHessianClassNoBatch(unittest.TestCase): ...@@ -490,6 +491,8 @@ class TestHessianClassNoBatch(unittest.TestCase):
self.rtol, self.atol) self.rtol, self.atol)
def func_create_graph_true(self): def func_create_graph_true(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
def func(x): def func(x):
return paddle.sum(F.sigmoid(x)) return paddle.sum(F.sigmoid(x))
...@@ -501,6 +504,7 @@ class TestHessianClassNoBatch(unittest.TestCase): ...@@ -501,6 +504,7 @@ class TestHessianClassNoBatch(unittest.TestCase):
assert hessian[:].stop_gradient == False assert hessian[:].stop_gradient == False
np.testing.assert_allclose(hessian[:].numpy(), numerical_hessian, np.testing.assert_allclose(hessian[:].numpy(), numerical_hessian,
self.rtol, self.atol) self.rtol, self.atol)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_out_not_single(self): def func_out_not_single(self):
def func(x): def func(x):
...@@ -733,6 +737,8 @@ class TestHessian(unittest.TestCase): ...@@ -733,6 +737,8 @@ class TestHessian(unittest.TestCase):
"does not appear") > 0 "does not appear") > 0
def func_create_graph_true(self): def func_create_graph_true(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
def func(x): def func(x):
return paddle.sum(F.sigmoid(x)) return paddle.sum(F.sigmoid(x))
...@@ -745,6 +751,7 @@ class TestHessian(unittest.TestCase): ...@@ -745,6 +751,7 @@ class TestHessian(unittest.TestCase):
self.rtol, self.atol) self.rtol, self.atol)
triple_grad = paddle.grad(hessian, self.x) triple_grad = paddle.grad(hessian, self.x)
assert triple_grad is not None assert triple_grad is not None
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_all_cases(self): def test_all_cases(self):
with _test_eager_guard(): with _test_eager_guard():
...@@ -1018,6 +1025,8 @@ class TestVHP(unittest.TestCase): ...@@ -1018,6 +1025,8 @@ class TestVHP(unittest.TestCase):
self.atol) self.atol)
def func_create_graph_true(self): def func_create_graph_true(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
def func(x): def func(x):
return paddle.sum(F.sigmoid(x)) return paddle.sum(F.sigmoid(x))
...@@ -1034,6 +1043,7 @@ class TestVHP(unittest.TestCase): ...@@ -1034,6 +1043,7 @@ class TestVHP(unittest.TestCase):
self.atol) self.atol)
triple_grad = paddle.grad(vhp, self.x) triple_grad = paddle.grad(vhp, self.x)
assert triple_grad is not None assert triple_grad is not None
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_all_cases(self): def test_all_cases(self):
with _test_eager_guard(): with _test_eager_guard():
...@@ -1102,6 +1112,8 @@ class TestJacobian(unittest.TestCase): ...@@ -1102,6 +1112,8 @@ class TestJacobian(unittest.TestCase):
self.atol) self.atol)
def func_multi_input_and_multi_output(self): def func_multi_input_and_multi_output(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
def func(x, y): def func(x, y):
return paddle.matmul(x, y), x * y return paddle.matmul(x, y), x * y
...@@ -1115,6 +1127,7 @@ class TestJacobian(unittest.TestCase): ...@@ -1115,6 +1127,7 @@ class TestJacobian(unittest.TestCase):
np.testing.assert_allclose(jacobian[i][j].numpy(), np.testing.assert_allclose(jacobian[i][j].numpy(),
numerical_jacobian[i][j], self.rtol, numerical_jacobian[i][j], self.rtol,
self.atol) self.atol)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_allow_unused_false(self): def func_allow_unused_false(self):
def func(x, y): def func(x, y):
......
python/paddle/fluid/tests/unittests/test_activation_nn_grad.py
浏览文件 @ 4d3b7d7d
...@@ -67,8 +67,10 @@ class TestSigmoidDoubleGradCheck(unittest.TestCase): ...@@ -67,8 +67,10 @@ class TestSigmoidDoubleGradCheck(unittest.TestCase):
x_arr[np.abs(x_arr) < 0.005] = 0.002 x_arr[np.abs(x_arr) < 0.005] = 0.002
gradient_checker.double_grad_check( gradient_checker.double_grad_check(
[x], y, x_init=x_arr, place=place, eps=eps) [x], y, x_init=x_arr, place=place, eps=eps)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
gradient_checker.double_grad_check_for_dygraph( gradient_checker.double_grad_check_for_dygraph(
self.sigmoid_wrapper, [x], y, x_init=x_arr, place=place) self.sigmoid_wrapper, [x], y, x_init=x_arr, place=place)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_grad(self): def test_grad(self):
paddle.enable_static() paddle.enable_static()
...@@ -95,8 +97,10 @@ class TestTanhTripleGradCheck(unittest.TestCase): ...@@ -95,8 +97,10 @@ class TestTanhTripleGradCheck(unittest.TestCase):
x_arr[np.abs(x_arr) < 0.005] = 0.002 x_arr[np.abs(x_arr) < 0.005] = 0.002
gradient_checker.triple_grad_check( gradient_checker.triple_grad_check(
[x], y, x_init=x_arr, place=place, eps=eps) [x], y, x_init=x_arr, place=place, eps=eps)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
gradient_checker.triple_grad_check_for_dygraph( gradient_checker.triple_grad_check_for_dygraph(
self.tanh_wrapper, [x], y, x_init=x_arr, place=place) self.tanh_wrapper, [x], y, x_init=x_arr, place=place)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_grad(self): def test_grad(self):
paddle.enable_static() paddle.enable_static()
...@@ -123,8 +127,10 @@ class TestTanhDoubleGradCheck(unittest.TestCase): ...@@ -123,8 +127,10 @@ class TestTanhDoubleGradCheck(unittest.TestCase):
x_arr[np.abs(x_arr) < 0.005] = 0.002 x_arr[np.abs(x_arr) < 0.005] = 0.002
gradient_checker.double_grad_check( gradient_checker.double_grad_check(
[x], y, x_init=x_arr, place=place, eps=eps) [x], y, x_init=x_arr, place=place, eps=eps)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
gradient_checker.double_grad_check_for_dygraph( gradient_checker.double_grad_check_for_dygraph(
self.tanh_wrapper, [x], y, x_init=x_arr, place=place) self.tanh_wrapper, [x], y, x_init=x_arr, place=place)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_grad(self): def test_grad(self):
paddle.enable_static() paddle.enable_static()
...@@ -151,8 +157,10 @@ class TestAbsDoubleGradCheck(unittest.TestCase): ...@@ -151,8 +157,10 @@ class TestAbsDoubleGradCheck(unittest.TestCase):
x_arr[np.abs(x_arr) < 0.005] = 0.002 x_arr[np.abs(x_arr) < 0.005] = 0.002
gradient_checker.double_grad_check( gradient_checker.double_grad_check(
[x], y, x_init=x_arr, place=place, eps=eps) [x], y, x_init=x_arr, place=place, eps=eps)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
gradient_checker.double_grad_check_for_dygraph( gradient_checker.double_grad_check_for_dygraph(
self.abs_wrapper, [x], y, x_init=x_arr, place=place) self.abs_wrapper, [x], y, x_init=x_arr, place=place)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_grad(self): def test_grad(self):
paddle.enable_static() paddle.enable_static()
...@@ -240,8 +248,10 @@ class TestELUDoubleGradCheck(unittest.TestCase): ...@@ -240,8 +248,10 @@ class TestELUDoubleGradCheck(unittest.TestCase):
x_arr = np.random.uniform(-1, 1, shape).astype(dtype) x_arr = np.random.uniform(-1, 1, shape).astype(dtype)
gradient_checker.double_grad_check( gradient_checker.double_grad_check(
[x], y, x_init=x_arr, place=place, eps=eps) [x], y, x_init=x_arr, place=place, eps=eps)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
gradient_checker.double_grad_check_for_dygraph( gradient_checker.double_grad_check_for_dygraph(
self.elu_wrapper, [x], y, x_init=x_arr, place=place) self.elu_wrapper, [x], y, x_init=x_arr, place=place)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_grad(self): def test_grad(self):
paddle.enable_static() paddle.enable_static()
...@@ -272,8 +282,10 @@ class TestCELUDoubleGradCheck(unittest.TestCase): ...@@ -272,8 +282,10 @@ class TestCELUDoubleGradCheck(unittest.TestCase):
x_arr = np.random.uniform(-1, 1, shape).astype(dtype) x_arr = np.random.uniform(-1, 1, shape).astype(dtype)
gradient_checker.double_grad_check( gradient_checker.double_grad_check(
[x], y, x_init=x_arr, place=place, eps=eps) [x], y, x_init=x_arr, place=place, eps=eps)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
gradient_checker.double_grad_check_for_dygraph( gradient_checker.double_grad_check_for_dygraph(
self.celu_wrapper, [x], y, x_init=x_arr, place=place) self.celu_wrapper, [x], y, x_init=x_arr, place=place)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_grad(self): def test_grad(self):
paddle.enable_static() paddle.enable_static()
...@@ -362,8 +374,10 @@ class TestSquareDoubleGradCheck(unittest.TestCase): ...@@ -362,8 +374,10 @@ class TestSquareDoubleGradCheck(unittest.TestCase):
gradient_checker.double_grad_check( gradient_checker.double_grad_check(
[x], y, x_init=x_arr, place=place, eps=eps) [x], y, x_init=x_arr, place=place, eps=eps)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
gradient_checker.double_grad_check_for_dygraph( gradient_checker.double_grad_check_for_dygraph(
self.square_wrapper, [x], y, x_init=x_arr, place=place) self.square_wrapper, [x], y, x_init=x_arr, place=place)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_grad(self): def test_grad(self):
paddle.enable_static() paddle.enable_static()
...@@ -421,8 +435,10 @@ class TestLogDoubleGradCheck(unittest.TestCase): ...@@ -421,8 +435,10 @@ class TestLogDoubleGradCheck(unittest.TestCase):
gradient_checker.double_grad_check( gradient_checker.double_grad_check(
[x], y, x_init=x_arr, place=place, eps=eps) [x], y, x_init=x_arr, place=place, eps=eps)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
gradient_checker.double_grad_check_for_dygraph( gradient_checker.double_grad_check_for_dygraph(
self.log_wrapper, [x], y, x_init=x_arr, place=place) self.log_wrapper, [x], y, x_init=x_arr, place=place)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_grad(self): def test_grad(self):
paddle.enable_static() paddle.enable_static()
......
python/paddle/fluid/tests/unittests/test_assign_op.py
浏览文件 @ 4d3b7d7d
...@@ -34,10 +34,14 @@ class TestAssignOp(op_test.OpTest): ...@@ -34,10 +34,14 @@ class TestAssignOp(op_test.OpTest):
self.outputs = {'Out': x} self.outputs = {'Out': x}
def test_forward(self): def test_forward(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
self.check_output(check_eager=True) self.check_output(check_eager=True)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_backward(self): def test_backward(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
self.check_grad(['X'], 'Out', check_eager=True) self.check_grad(['X'], 'Out', check_eager=True)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
class TestAssignFP16Op(op_test.OpTest): class TestAssignFP16Op(op_test.OpTest):
...@@ -49,14 +53,19 @@ class TestAssignFP16Op(op_test.OpTest): ...@@ -49,14 +53,19 @@ class TestAssignFP16Op(op_test.OpTest):
self.outputs = {'Out': x} self.outputs = {'Out': x}
def test_forward(self): def test_forward(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
self.check_output(check_eager=True) self.check_output(check_eager=True)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_backward(self): def test_backward(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
self.check_grad(['X'], 'Out', check_eager=True) self.check_grad(['X'], 'Out', check_eager=True)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
class TestAssignOpWithLoDTensorArray(unittest.TestCase): class TestAssignOpWithLoDTensorArray(unittest.TestCase):
def test_assign_LoDTensorArray(self): def test_assign_LoDTensorArray(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
main_program = Program() main_program = Program()
startup_program = Program() startup_program = Program()
with program_guard(main_program): with program_guard(main_program):
...@@ -71,6 +80,7 @@ class TestAssignOpWithLoDTensorArray(unittest.TestCase): ...@@ -71,6 +80,7 @@ class TestAssignOpWithLoDTensorArray(unittest.TestCase):
sums = fluid.layers.array_read(array=init_array, i=i) sums = fluid.layers.array_read(array=init_array, i=i)
mean = fluid.layers.mean(sums) mean = fluid.layers.mean(sums)
append_backward(mean) append_backward(mean)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
place = fluid.CUDAPlace(0) if core.is_compiled_with_cuda( place = fluid.CUDAPlace(0) if core.is_compiled_with_cuda(
) else fluid.CPUPlace() ) else fluid.CPUPlace()
...@@ -173,6 +183,7 @@ class TestAssignOApi(unittest.TestCase): ...@@ -173,6 +183,7 @@ class TestAssignOApi(unittest.TestCase):
def test_clone(self): def test_clone(self):
paddle.disable_static() paddle.disable_static()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
self.python_api = paddle.clone self.python_api = paddle.clone
x = paddle.ones([2]) x = paddle.ones([2])
...@@ -185,6 +196,7 @@ class TestAssignOApi(unittest.TestCase): ...@@ -185,6 +196,7 @@ class TestAssignOApi(unittest.TestCase):
self.assertTrue(np.array_equal(x, [1, 1]), True) self.assertTrue(np.array_equal(x, [1, 1]), True)
self.assertTrue(np.array_equal(clone_x.grad.numpy(), [3, 3]), True) self.assertTrue(np.array_equal(clone_x.grad.numpy(), [3, 3]), True)
self.assertTrue(np.array_equal(x.grad.numpy(), [3, 3]), True) self.assertTrue(np.array_equal(x.grad.numpy(), [3, 3]), True)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
paddle.enable_static() paddle.enable_static()
with program_guard(Program(), Program()): with program_guard(Program(), Program()):
...@@ -201,6 +213,7 @@ class TestAssignOApi(unittest.TestCase): ...@@ -201,6 +213,7 @@ class TestAssignOApi(unittest.TestCase):
class TestAssignOpErrorApi(unittest.TestCase): class TestAssignOpErrorApi(unittest.TestCase):
def test_errors(self): def test_errors(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with program_guard(Program(), Program()): with program_guard(Program(), Program()):
# The type of input must be Variable or numpy.ndarray. # The type of input must be Variable or numpy.ndarray.
x1 = fluid.create_lod_tensor( x1 = fluid.create_lod_tensor(
...@@ -209,6 +222,7 @@ class TestAssignOpErrorApi(unittest.TestCase): ...@@ -209,6 +222,7 @@ class TestAssignOpErrorApi(unittest.TestCase):
# When the type of input is numpy.ndarray, the dtype of input must be float32, int32. # When the type of input is numpy.ndarray, the dtype of input must be float32, int32.
x2 = np.array([[2.5, 2.5]], dtype='uint8') x2 = np.array([[2.5, 2.5]], dtype='uint8')
self.assertRaises(TypeError, paddle.assign, x2) self.assertRaises(TypeError, paddle.assign, x2)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_type_error(self): def test_type_error(self):
paddle.enable_static() paddle.enable_static()
......
python/paddle/fluid/tests/unittests/test_detach.py
浏览文件 @ 4d3b7d7d
...@@ -139,10 +139,12 @@ class Test_Detach(unittest.TestCase): ...@@ -139,10 +139,12 @@ class Test_Detach(unittest.TestCase):
return x.gradient() return x.gradient()
def test_NoDetachMulti_DetachMulti(self): def test_NoDetachMulti_DetachMulti(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
array_no_detach_multi = self.no_detach_multi() array_no_detach_multi = self.no_detach_multi()
array_detach_multi = self.detach_multi() array_detach_multi = self.detach_multi()
assert not np.array_equal(array_no_detach_multi, array_detach_multi) assert not np.array_equal(array_no_detach_multi, array_detach_multi)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_NoDetachSingle_DetachMulti(self): def test_NoDetachSingle_DetachMulti(self):
array_no_detach_single = self.no_detach_single() array_no_detach_single = self.no_detach_single()
......
python/paddle/fluid/tests/unittests/test_elementwise_nn_grad.py
浏览文件 @ 4d3b7d7d
...@@ -346,11 +346,13 @@ class TestElementwiseMulTripleGradCheck(unittest.TestCase): ...@@ -346,11 +346,13 @@ class TestElementwiseMulTripleGradCheck(unittest.TestCase):
gradient_checker.triple_grad_check( gradient_checker.triple_grad_check(
[x, y], out, x_init=[x_arr, y_arr], place=place, eps=eps) [x, y], out, x_init=[x_arr, y_arr], place=place, eps=eps)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
gradient_checker.triple_grad_check_for_dygraph( gradient_checker.triple_grad_check_for_dygraph(
self.multiply_wrapper, [x, y], self.multiply_wrapper, [x, y],
out, out,
x_init=[x_arr, y_arr], x_init=[x_arr, y_arr],
place=place) place=place)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_grad(self): def test_grad(self):
paddle.enable_static() paddle.enable_static()
......
python/paddle/fluid/tests/unittests/test_elementwise_pow_op.py
浏览文件 @ 4d3b7d7d
...@@ -185,6 +185,7 @@ class TestElementwisePowGradOpInt(unittest.TestCase): ...@@ -185,6 +185,7 @@ class TestElementwisePowGradOpInt(unittest.TestCase):
print(self.grad_res, self.grad_x, self.grad_y) print(self.grad_res, self.grad_x, self.grad_y)
def test_grad(self): def test_grad(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
places = [fluid.CPUPlace()] places = [fluid.CPUPlace()]
if fluid.is_compiled_with_cuda(): if fluid.is_compiled_with_cuda():
places.append(fluid.CUDAPlace(0)) places.append(fluid.CUDAPlace(0))
...@@ -200,6 +201,7 @@ class TestElementwisePowGradOpInt(unittest.TestCase): ...@@ -200,6 +201,7 @@ class TestElementwisePowGradOpInt(unittest.TestCase):
self.assertTrue(np.array_equal(res.gradient(), self.grad_res)) self.assertTrue(np.array_equal(res.gradient(), self.grad_res))
self.assertTrue(np.array_equal(x.gradient(), self.grad_x)) self.assertTrue(np.array_equal(x.gradient(), self.grad_x))
self.assertTrue(np.array_equal(y.gradient(), self.grad_y)) self.assertTrue(np.array_equal(y.gradient(), self.grad_y))
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
if __name__ == '__main__': if __name__ == '__main__':
......
python/paddle/fluid/tests/unittests/test_imperative_auto_prune.py
浏览文件 @ 4d3b7d7d
...@@ -195,9 +195,11 @@ class TestImperativeAutoPrune(unittest.TestCase): ...@@ -195,9 +195,11 @@ class TestImperativeAutoPrune(unittest.TestCase):
self.assertTrue((part2.gradient() == 0).all()) self.assertTrue((part2.gradient() == 0).all())
def test_auto_prune3(self): def test_auto_prune3(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_auto_prune3() self.func_auto_prune3()
self.func_auto_prune3() self.func_auto_prune3()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_auto_prune4(self): def func_auto_prune4(self):
with fluid.dygraph.guard(): with fluid.dygraph.guard():
...@@ -212,9 +214,11 @@ class TestImperativeAutoPrune(unittest.TestCase): ...@@ -212,9 +214,11 @@ class TestImperativeAutoPrune(unittest.TestCase):
self.assertTrue((part2.gradient() == 1).all()) self.assertTrue((part2.gradient() == 1).all())
def test_auto_prune4(self): def test_auto_prune4(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_auto_prune4() self.func_auto_prune4()
self.func_auto_prune4() self.func_auto_prune4()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_auto_prune5(self): def func_auto_prune5(self):
with fluid.dygraph.guard(): with fluid.dygraph.guard():
...@@ -229,9 +233,11 @@ class TestImperativeAutoPrune(unittest.TestCase): ...@@ -229,9 +233,11 @@ class TestImperativeAutoPrune(unittest.TestCase):
self.assertTrue((part2.gradient() == 0).all()) self.assertTrue((part2.gradient() == 0).all())
def test_auto_prune5(self): def test_auto_prune5(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_auto_prune5() self.func_auto_prune5()
self.func_auto_prune5() self.func_auto_prune5()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_auto_prune6(self): def func_auto_prune6(self):
with fluid.dygraph.guard(): with fluid.dygraph.guard():
......
python/paddle/fluid/tests/unittests/test_imperative_basic.py
浏览文件 @ 4d3b7d7d
...@@ -479,9 +479,11 @@ class TestImperative(unittest.TestCase): ...@@ -479,9 +479,11 @@ class TestImperative(unittest.TestCase):
self.assertTrue(np.array_equal(dy_grad2, static_grad)) self.assertTrue(np.array_equal(dy_grad2, static_grad))
def test_layer_in_out(self): def test_layer_in_out(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_layer_in_out() self.func_layer_in_out()
self.func_layer_in_out() self.func_layer_in_out()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_mlp(self): def func_mlp(self):
np_inp = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32) np_inp = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32)
......
python/paddle/fluid/tests/unittests/test_imperative_recurrent_usage.py
浏览文件 @ 4d3b7d7d
...@@ -45,6 +45,7 @@ class TestRecurrentFeed(unittest.TestCase): ...@@ -45,6 +45,7 @@ class TestRecurrentFeed(unittest.TestCase):
original_np1 = np.arange(1, 5).reshape(2, 2).astype("float32") original_np1 = np.arange(1, 5).reshape(2, 2).astype("float32")
original_np2 = np.arange(5, 9).reshape(2, 2).astype("float32") original_np2 = np.arange(5, 9).reshape(2, 2).astype("float32")
with fluid.dygraph.guard(): with fluid.dygraph.guard():
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
fluid.default_startup_program().random_seed = seed fluid.default_startup_program().random_seed = seed
fluid.default_main_program().random_seed = seed fluid.default_main_program().random_seed = seed
original_in1 = to_variable(original_np1) original_in1 = to_variable(original_np1)
...@@ -61,8 +62,10 @@ class TestRecurrentFeed(unittest.TestCase): ...@@ -61,8 +62,10 @@ class TestRecurrentFeed(unittest.TestCase):
dyout = out.gradient() dyout = out.gradient()
original_in1.stop_gradient = True original_in1.stop_gradient = True
rt.clear_gradients() rt.clear_gradients()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
with fluid.dygraph.guard(): with fluid.dygraph.guard():
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
fluid.default_startup_program().random_seed = seed fluid.default_startup_program().random_seed = seed
fluid.default_main_program().random_seed = seed fluid.default_main_program().random_seed = seed
...@@ -80,6 +83,7 @@ class TestRecurrentFeed(unittest.TestCase): ...@@ -80,6 +83,7 @@ class TestRecurrentFeed(unittest.TestCase):
eager_dyout = out.gradient() eager_dyout = out.gradient()
original_in1.stop_gradient = True original_in1.stop_gradient = True
rt.clear_gradients() rt.clear_gradients()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
with new_program_scope(): with new_program_scope():
fluid.default_startup_program().random_seed = seed fluid.default_startup_program().random_seed = seed
......
python/paddle/fluid/tests/unittests/test_imperative_selected_rows.py
浏览文件 @ 4d3b7d7d
...@@ -79,9 +79,11 @@ class TestSimpleNet(unittest.TestCase): ...@@ -79,9 +79,11 @@ class TestSimpleNet(unittest.TestCase):
paddle.enable_static() paddle.enable_static()
def test_selectedrows_gradient1(self): def test_selectedrows_gradient1(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_selectedrows_gradient1() self.func_selectedrows_gradient1()
self.func_selectedrows_gradient1() self.func_selectedrows_gradient1()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_selectedrows_gradient2(self): def func_selectedrows_gradient2(self):
places = [fluid.CPUPlace()] places = [fluid.CPUPlace()]
...@@ -120,9 +122,11 @@ class TestSimpleNet(unittest.TestCase): ...@@ -120,9 +122,11 @@ class TestSimpleNet(unittest.TestCase):
self.assertTrue(input_emb.gradient() is not None) self.assertTrue(input_emb.gradient() is not None)
def test_selectedrows_gradient2(self): def test_selectedrows_gradient2(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_selectedrows_gradient2() self.func_selectedrows_gradient2()
self.func_selectedrows_gradient2() self.func_selectedrows_gradient2()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
if __name__ == '__main__': if __name__ == '__main__':
......
python/paddle/fluid/tests/unittests/test_imperative_triple_grad.py
浏览文件 @ 4d3b7d7d
...@@ -209,11 +209,13 @@ class TestDygraphTripleGrad(TestCase): ...@@ -209,11 +209,13 @@ class TestDygraphTripleGrad(TestCase):
self.assertTrue(np.allclose(dddx_grad_actual, dddx_expected)) self.assertTrue(np.allclose(dddx_grad_actual, dddx_expected))
def test_all_cases(self): def test_all_cases(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
self.func_exception() self.func_exception()
self.func_example_with_gradient_and_create_graph() self.func_example_with_gradient_and_create_graph()
with _test_eager_guard(): with _test_eager_guard():
self.func_exception() self.func_exception()
self.func_example_with_gradient_and_create_graph() self.func_example_with_gradient_and_create_graph()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
class TestDygraphTripleGradBradcastCase(TestCase): class TestDygraphTripleGradBradcastCase(TestCase):
...@@ -298,9 +300,11 @@ class TestDygraphTripleGradBradcastCase(TestCase): ...@@ -298,9 +300,11 @@ class TestDygraphTripleGradBradcastCase(TestCase):
self.assertTrue(np.allclose(dddx_grad_actual, dddx_expected)) self.assertTrue(np.allclose(dddx_grad_actual, dddx_expected))
def test_all_cases(self): def test_all_cases(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
self.func_example_with_gradient_and_create_graph() self.func_example_with_gradient_and_create_graph()
with _test_eager_guard(): with _test_eager_guard():
self.func_example_with_gradient_and_create_graph() self.func_example_with_gradient_and_create_graph()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
if __name__ == '__main__': if __name__ == '__main__':
......
python/paddle/fluid/tests/unittests/test_op_function_generator.py
浏览文件 @ 4d3b7d7d
...@@ -74,6 +74,7 @@ class TestVariable(unittest.TestCase): ...@@ -74,6 +74,7 @@ class TestVariable(unittest.TestCase):
self.assertTrue(np.array_equal(res1.numpy(), res2.numpy())) self.assertTrue(np.array_equal(res1.numpy(), res2.numpy()))
def test_trace_backward(self): def test_trace_backward(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with fluid.dygraph.guard(): with fluid.dygraph.guard():
a = np.random.uniform(0.1, 1, self.shape).astype(self.dtype) a = np.random.uniform(0.1, 1, self.shape).astype(self.dtype)
b = np.random.uniform(0.1, 1, self.shape).astype(self.dtype) b = np.random.uniform(0.1, 1, self.shape).astype(self.dtype)
...@@ -90,6 +91,7 @@ class TestVariable(unittest.TestCase): ...@@ -90,6 +91,7 @@ class TestVariable(unittest.TestCase):
self.assertTrue(np.array_equal(x_grad, loss.gradient() * b)) self.assertTrue(np.array_equal(x_grad, loss.gradient() * b))
self.assertTrue(np.array_equal(y_grad, loss.gradient() * a)) self.assertTrue(np.array_equal(y_grad, loss.gradient() * a))
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_traced_layer(self): def test_traced_layer(self):
if in_dygraph_mode(): if in_dygraph_mode():
......
python/paddle/fluid/tests/unittests/test_set_value_op.py
浏览文件 @ 4d3b7d7d
...@@ -20,6 +20,7 @@ import unittest ...@@ -20,6 +20,7 @@ import unittest
import numpy as np import numpy as np
import paddle import paddle
import paddle.fluid as fluid
from paddle.fluid.layer_helper import LayerHelper from paddle.fluid.layer_helper import LayerHelper
from functools import reduce from functools import reduce
from paddle.fluid.framework import _test_eager_guard, _in_legacy_dygraph from paddle.fluid.framework import _test_eager_guard, _in_legacy_dygraph
...@@ -1014,9 +1015,11 @@ class TestBackward(unittest.TestCase): ...@@ -1014,9 +1015,11 @@ class TestBackward(unittest.TestCase):
self.assertTrue((0 == x.grad[0, :, 0, 0]).all()) self.assertTrue((0 == x.grad[0, :, 0, 0]).all())
def test_dynamic(self): def test_dynamic(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_test_dynamic() self.func_test_dynamic()
self.func_test_dynamic() self.func_test_dynamic()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
class TestGradientTruncated(unittest.TestCase): class TestGradientTruncated(unittest.TestCase):
......
python/paddle/fluid/tests/unittests/test_sparse_norm_op.py
浏览文件 @ 4d3b7d7d
...@@ -16,12 +16,14 @@ from __future__ import print_function ...@@ -16,12 +16,14 @@ from __future__ import print_function
import unittest import unittest
import numpy as np import numpy as np
import paddle import paddle
import paddle.fluid as fluid
from paddle.fluid.framework import _test_eager_guard from paddle.fluid.framework import _test_eager_guard
import copy import copy
class TestSparseBatchNorm(unittest.TestCase): class TestSparseBatchNorm(unittest.TestCase):
def test(self): def test(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
paddle.seed(0) paddle.seed(0)
channels = 4 channels = 4
...@@ -59,6 +61,7 @@ class TestSparseBatchNorm(unittest.TestCase): ...@@ -59,6 +61,7 @@ class TestSparseBatchNorm(unittest.TestCase):
sparse_x.grad.values().flatten().numpy(), sparse_x.grad.values().flatten().numpy(),
atol=1e-5, atol=1e-5,
rtol=1e-5) rtol=1e-5)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_error_layout(self): def test_error_layout(self):
with _test_eager_guard(): with _test_eager_guard():
......
python/paddle/fluid/tests/unittests/test_sparse_unary_op.py
浏览文件 @ 4d3b7d7d
...@@ -17,6 +17,7 @@ import unittest ...@@ -17,6 +17,7 @@ import unittest
from typing import Union, Callable from typing import Union, Callable
import numpy as np import numpy as np
import paddle import paddle
import paddle.fluid as fluid
from paddle.fluid.framework import _test_eager_guard from paddle.fluid.framework import _test_eager_guard
from paddle import _C_ops from paddle import _C_ops
...@@ -42,6 +43,7 @@ class TestSparseUnary(unittest.TestCase): ...@@ -42,6 +43,7 @@ class TestSparseUnary(unittest.TestCase):
return np.allclose(dense_numpy[mask], return np.allclose(dense_numpy[mask],
sparse_tensor.to_dense().numpy()[mask]) sparse_tensor.to_dense().numpy()[mask])
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
dense_x = paddle.to_tensor( dense_x = paddle.to_tensor(
x, dtype="float32", stop_gradient=not test_gradient) x, dtype="float32", stop_gradient=not test_gradient)
...@@ -59,6 +61,7 @@ class TestSparseUnary(unittest.TestCase): ...@@ -59,6 +61,7 @@ class TestSparseUnary(unittest.TestCase):
dense_out.backward(dense_out) dense_out.backward(dense_out)
sparse_out.backward(sparse_out) sparse_out.backward(sparse_out)
assert tensor_allclose(dense_x.grad, sparse_x.grad) assert tensor_allclose(dense_x.grad, sparse_x.grad)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_sparse_relu(self): def test_sparse_relu(self):
x = [[0, -1, 0, 2], [0, 0, -3, 0], [4, 5, 0, 0]] x = [[0, -1, 0, 2], [0, 0, -3, 0], [4, 5, 0, 0]]
......
python/paddle/fluid/tests/unittests/test_sparse_utils_op.py
浏览文件 @ 4d3b7d7d
...@@ -16,6 +16,7 @@ from __future__ import print_function ...@@ -16,6 +16,7 @@ from __future__ import print_function
import unittest import unittest
import numpy as np import numpy as np
import paddle import paddle
import paddle.fluid as fluid
import paddle.fluid.core as core import paddle.fluid.core as core
from paddle.fluid.framework import _test_eager_guard from paddle.fluid.framework import _test_eager_guard
...@@ -151,6 +152,7 @@ class TestSparseConvert(unittest.TestCase): ...@@ -151,6 +152,7 @@ class TestSparseConvert(unittest.TestCase):
out_grad.to_dense().numpy()) out_grad.to_dense().numpy())
def test_coo_to_dense(self): def test_coo_to_dense(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
indices = [[0, 0, 1, 2, 2], [1, 3, 2, 0, 1]] indices = [[0, 0, 1, 2, 2], [1, 3, 2, 0, 1]]
values = [1.0, 2.0, 3.0, 4.0, 5.0] values = [1.0, 2.0, 3.0, 4.0, 5.0]
...@@ -179,6 +181,7 @@ class TestSparseConvert(unittest.TestCase): ...@@ -179,6 +181,7 @@ class TestSparseConvert(unittest.TestCase):
dense_tensor_cpu.backward(paddle.to_tensor(out_grad)) dense_tensor_cpu.backward(paddle.to_tensor(out_grad))
assert np.array_equal(correct_x_grad, assert np.array_equal(correct_x_grad,
sparse_x_cpu.grad.values().numpy()) sparse_x_cpu.grad.values().numpy())
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_to_sparse_csr(self): def test_to_sparse_csr(self):
with _test_eager_guard(): with _test_eager_guard():
...@@ -196,6 +199,7 @@ class TestSparseConvert(unittest.TestCase): ...@@ -196,6 +199,7 @@ class TestSparseConvert(unittest.TestCase):
assert np.array_equal(dense_tensor.numpy(), x) assert np.array_equal(dense_tensor.numpy(), x)
def test_coo_values_grad(self): def test_coo_values_grad(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
indices = [[0, 0, 1, 2, 2], [1, 3, 2, 0, 1]] indices = [[0, 0, 1, 2, 2], [1, 3, 2, 0, 1]]
values = [1.0, 2.0, 3.0, 4.0, 5.0] values = [1.0, 2.0, 3.0, 4.0, 5.0]
...@@ -223,6 +227,7 @@ class TestSparseConvert(unittest.TestCase): ...@@ -223,6 +227,7 @@ class TestSparseConvert(unittest.TestCase):
# test coo_values_grad # test coo_values_grad
values_tensor.backward(paddle.to_tensor(out_grad)) values_tensor.backward(paddle.to_tensor(out_grad))
assert np.array_equal(out_grad, sparse_x.grad.values().numpy()) assert np.array_equal(out_grad, sparse_x.grad.values().numpy())
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_sparse_coo_tensor_grad(self): def test_sparse_coo_tensor_grad(self):
with _test_eager_guard(): with _test_eager_guard():
......
python/paddle/fluid/tests/unittests/test_tensor_fill_.py
浏览文件 @ 4d3b7d7d
...@@ -78,9 +78,11 @@ class TensorFill_Test(unittest.TestCase): ...@@ -78,9 +78,11 @@ class TensorFill_Test(unittest.TestCase):
self.assertEqual((y.grad.numpy() == 0).all().item(), True) self.assertEqual((y.grad.numpy() == 0).all().item(), True)
def test_tensor_fill_backward(self): def test_tensor_fill_backward(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_test_tensor_fill_backward() self.func_test_tensor_fill_backward()
self.func_test_tensor_fill_backward() self.func_test_tensor_fill_backward()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_test_errors(self): def func_test_errors(self):
def test_list(): def test_list():
......
python/paddle/fluid/tests/unittests/test_tensor_fill_diagonal_.py
浏览文件 @ 4d3b7d7d
...@@ -52,9 +52,11 @@ class TensorFillDiagonal_Test(unittest.TestCase): ...@@ -52,9 +52,11 @@ class TensorFillDiagonal_Test(unittest.TestCase):
True) True)
def test_dim2_normal(self): def test_dim2_normal(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_dim2_normal() self.func_dim2_normal()
self.func_dim2_normal() self.func_dim2_normal()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_offset(self): def func_offset(self):
expected_np = np.array( expected_np = np.array(
...@@ -87,9 +89,11 @@ class TensorFillDiagonal_Test(unittest.TestCase): ...@@ -87,9 +89,11 @@ class TensorFillDiagonal_Test(unittest.TestCase):
True) True)
def test_offset(self): def test_offset(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_offset() self.func_offset()
self.func_offset() self.func_offset()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_bool(self): def func_bool(self):
expected_np = np.array( expected_np = np.array(
...@@ -150,9 +154,11 @@ class TensorFillDiagonal_Test(unittest.TestCase): ...@@ -150,9 +154,11 @@ class TensorFillDiagonal_Test(unittest.TestCase):
True) True)
def test_dim2_unnormal_wrap(self): def test_dim2_unnormal_wrap(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_dim2_unnormal_wrap() self.func_dim2_unnormal_wrap()
self.func_dim2_unnormal_wrap() self.func_dim2_unnormal_wrap()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_dim2_unnormal_unwrap(self): def func_dim2_unnormal_unwrap(self):
expected_np = np.array([[1, 2, 2], [2, 1, 2], [2, 2, 1], [2, 2, 2], expected_np = np.array([[1, 2, 2], [2, 1, 2], [2, 2, 1], [2, 2, 2],
...@@ -187,9 +193,11 @@ class TensorFillDiagonal_Test(unittest.TestCase): ...@@ -187,9 +193,11 @@ class TensorFillDiagonal_Test(unittest.TestCase):
True) True)
def test_dim2_unnormal_unwrap(self): def test_dim2_unnormal_unwrap(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_dim2_unnormal_unwrap() self.func_dim2_unnormal_unwrap()
self.func_dim2_unnormal_unwrap() self.func_dim2_unnormal_unwrap()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_dim_larger2_normal(self): def func_dim_larger2_normal(self):
expected_np = np.array([[[1, 2, 2], [2, 2, 2], [2, 2, 2]], [[2, 2, 2], [ expected_np = np.array([[[1, 2, 2], [2, 2, 2], [2, 2, 2]], [[2, 2, 2], [
...@@ -225,9 +233,11 @@ class TensorFillDiagonal_Test(unittest.TestCase): ...@@ -225,9 +233,11 @@ class TensorFillDiagonal_Test(unittest.TestCase):
True) True)
def test_dim_larger2_normal(self): def test_dim_larger2_normal(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_dim_larger2_normal() self.func_dim_larger2_normal()
self.func_dim_larger2_normal() self.func_dim_larger2_normal()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
if __name__ == '__main__': if __name__ == '__main__':
......
python/paddle/fluid/tests/unittests/test_tensor_fill_diagonal_tensor.py
浏览文件 @ 4d3b7d7d
...@@ -28,6 +28,7 @@ class TensorFillDiagTensor_Test(unittest.TestCase): ...@@ -28,6 +28,7 @@ class TensorFillDiagTensor_Test(unittest.TestCase):
self.places.append(fluid.CUDAPlace(0)) self.places.append(fluid.CUDAPlace(0))
def test_dim2(self): def test_dim2(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
expected_np = np.array( expected_np = np.array(
[[1, 2, 2], [2, 1, 2], [2, 2, 1], [2, 2, 2]]).astype('float32') [[1, 2, 2], [2, 1, 2], [2, 2, 1], [2, 2, 2]]).astype('float32')
expected_grad = np.array( expected_grad = np.array(
...@@ -53,8 +54,10 @@ class TensorFillDiagTensor_Test(unittest.TestCase): ...@@ -53,8 +54,10 @@ class TensorFillDiagTensor_Test(unittest.TestCase):
self.assertEqual( self.assertEqual(
(y.grad.numpy().astype('float32') == expected_grad).all(), (y.grad.numpy().astype('float32') == expected_grad).all(),
True) True)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_dim2_offset_1(self): def test_dim2_offset_1(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
expected_np = np.array( expected_np = np.array(
[[2, 2, 2], [1, 2, 2], [2, 1, 2], [2, 2, 1]]).astype('float32') [[2, 2, 2], [1, 2, 2], [2, 1, 2], [2, 2, 1]]).astype('float32')
expected_grad = np.array( expected_grad = np.array(
...@@ -80,8 +83,10 @@ class TensorFillDiagTensor_Test(unittest.TestCase): ...@@ -80,8 +83,10 @@ class TensorFillDiagTensor_Test(unittest.TestCase):
self.assertEqual( self.assertEqual(
(y.grad.numpy().astype('float32') == expected_grad).all(), (y.grad.numpy().astype('float32') == expected_grad).all(),
True) True)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_dim2_offset1(self): def test_dim2_offset1(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
expected_np = np.array( expected_np = np.array(
[[2, 1, 2], [2, 2, 1], [2, 2, 2], [2, 2, 2]]).astype('float32') [[2, 1, 2], [2, 2, 1], [2, 2, 2], [2, 2, 2]]).astype('float32')
expected_grad = np.array( expected_grad = np.array(
...@@ -107,8 +112,10 @@ class TensorFillDiagTensor_Test(unittest.TestCase): ...@@ -107,8 +112,10 @@ class TensorFillDiagTensor_Test(unittest.TestCase):
self.assertEqual( self.assertEqual(
(y.grad.numpy().astype('float32') == expected_grad).all(), (y.grad.numpy().astype('float32') == expected_grad).all(),
True) True)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_dim4(self): def test_dim4(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
expected_np = np.array( expected_np = np.array(
[[[[0, 3], [2, 2], [2, 2]], [[2, 2], [1, 4], [2, 2]], [[[[0, 3], [2, 2], [2, 2]], [[2, 2], [1, 4], [2, 2]],
[[2, 2], [2, 2], [2, 5]], [[2, 2], [2, 2], [2, 2]]], [[2, 2], [2, 2], [2, 5]], [[2, 2], [2, 2], [2, 2]]],
...@@ -143,6 +150,7 @@ class TensorFillDiagTensor_Test(unittest.TestCase): ...@@ -143,6 +150,7 @@ class TensorFillDiagTensor_Test(unittest.TestCase):
self.assertEqual( self.assertEqual(
(y.grad.numpy().astype('float32') == expected_grad).all(), (y.grad.numpy().astype('float32') == expected_grad).all(),
True) True)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def test_largedim(self): def test_largedim(self):
if len(self.places) > 1: if len(self.places) > 1:
......
python/paddle/fluid/tests/unittests/test_tensor_fill_diagonal_tensor_.py
浏览文件 @ 4d3b7d7d
...@@ -56,9 +56,11 @@ class TensorFillDiagTensor_Test(unittest.TestCase): ...@@ -56,9 +56,11 @@ class TensorFillDiagTensor_Test(unittest.TestCase):
True) True)
def test_dim2(self): def test_dim2(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_dim2() self.func_dim2()
self.func_dim2() self.func_dim2()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_dim2_offset_1(self): def func_dim2_offset_1(self):
expected_np = np.array( expected_np = np.array(
...@@ -88,9 +90,11 @@ class TensorFillDiagTensor_Test(unittest.TestCase): ...@@ -88,9 +90,11 @@ class TensorFillDiagTensor_Test(unittest.TestCase):
True) True)
def test_dim2_offset_1(self): def test_dim2_offset_1(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_dim2_offset_1() self.func_dim2_offset_1()
self.func_dim2_offset_1() self.func_dim2_offset_1()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_dim2_offset1(self): def func_dim2_offset1(self):
expected_np = np.array( expected_np = np.array(
...@@ -120,9 +124,11 @@ class TensorFillDiagTensor_Test(unittest.TestCase): ...@@ -120,9 +124,11 @@ class TensorFillDiagTensor_Test(unittest.TestCase):
True) True)
def test_dim2_offset1(self): def test_dim2_offset1(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_dim2_offset1() self.func_dim2_offset1()
self.func_dim2_offset1() self.func_dim2_offset1()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_dim4(self): def func_dim4(self):
expected_np = np.array( expected_np = np.array(
...@@ -161,9 +167,11 @@ class TensorFillDiagTensor_Test(unittest.TestCase): ...@@ -161,9 +167,11 @@ class TensorFillDiagTensor_Test(unittest.TestCase):
True) True)
def test_func_dim4(self): def test_func_dim4(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_dim4() self.func_dim4()
self.func_dim4() self.func_dim4()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_largedim(self): def func_largedim(self):
#large dim only test on gpu because the cpu version is too slow for ci test, and the memory is limited #large dim only test on gpu because the cpu version is too slow for ci test, and the memory is limited
...@@ -190,9 +198,11 @@ class TensorFillDiagTensor_Test(unittest.TestCase): ...@@ -190,9 +198,11 @@ class TensorFillDiagTensor_Test(unittest.TestCase):
self.assertEqual((y.grad == expected_grad).all(), True) self.assertEqual((y.grad == expected_grad).all(), True)
def test_largedim(self): def test_largedim(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_largedim() self.func_largedim()
self.func_largedim() self.func_largedim()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
if __name__ == '__main__': if __name__ == '__main__':
......
python/paddle/fluid/tests/unittests/test_tensor_register_hook.py
浏览文件 @ 4d3b7d7d
...@@ -158,9 +158,11 @@ class TestTensorRegisterHook(unittest.TestCase): ...@@ -158,9 +158,11 @@ class TestTensorRegisterHook(unittest.TestCase):
run_print_hook_for_interior_var(print_hook, removed=True) run_print_hook_for_interior_var(print_hook, removed=True)
def test_hook_for_interior_var(self): def test_hook_for_interior_var(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_hook_for_interior_var() self.func_hook_for_interior_var()
self.func_hook_for_interior_var() self.func_hook_for_interior_var()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_hook_for_leaf_var(self): def func_hook_for_leaf_var(self):
def run_double_hook_for_leaf_var(double_hook, removed=False): def run_double_hook_for_leaf_var(double_hook, removed=False):
...@@ -202,9 +204,11 @@ class TestTensorRegisterHook(unittest.TestCase): ...@@ -202,9 +204,11 @@ class TestTensorRegisterHook(unittest.TestCase):
run_double_hook_for_leaf_var(lambda grad: grad * 2, removed=True) run_double_hook_for_leaf_var(lambda grad: grad * 2, removed=True)
def test_hook_for_leaf_var(self): def test_hook_for_leaf_var(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_hook_for_leaf_var() self.func_hook_for_leaf_var()
self.func_hook_for_leaf_var() self.func_hook_for_leaf_var()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_hook_for_accumulated_grad_interior_var(self): def func_hook_for_accumulated_grad_interior_var(self):
def run_double_hook_for_accumulated_grad_interior_var(double_hook, def run_double_hook_for_accumulated_grad_interior_var(double_hook,
...@@ -262,9 +266,11 @@ class TestTensorRegisterHook(unittest.TestCase): ...@@ -262,9 +266,11 @@ class TestTensorRegisterHook(unittest.TestCase):
lambda grad: grad * 2, removed=True) lambda grad: grad * 2, removed=True)
def test_hook_for_accumulated_grad_interior_var(self): def test_hook_for_accumulated_grad_interior_var(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_hook_for_accumulated_grad_interior_var() self.func_hook_for_accumulated_grad_interior_var()
self.func_hook_for_accumulated_grad_interior_var() self.func_hook_for_accumulated_grad_interior_var()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_hook_for_accumulated_grad_leaf_var(self): def func_hook_for_accumulated_grad_leaf_var(self):
def run_double_hook_for_accumulated_grad_leaf_var(double_hook, def run_double_hook_for_accumulated_grad_leaf_var(double_hook,
...@@ -360,9 +366,11 @@ class TestTensorRegisterHook(unittest.TestCase): ...@@ -360,9 +366,11 @@ class TestTensorRegisterHook(unittest.TestCase):
self.assertTrue(np.array_equal(linear1_b_grad, linear1_b_grad_rm)) self.assertTrue(np.array_equal(linear1_b_grad, linear1_b_grad_rm))
def test_func_hook_in_model(self): def test_func_hook_in_model(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_hook_in_model() self.func_hook_in_model()
self.func_hook_in_model() self.func_hook_in_model()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_multiple_hooks_for_interior_var(self): def func_multiple_hooks_for_interior_var(self):
def run_multiple_hooks_for_interior_var(device, def run_multiple_hooks_for_interior_var(device,
...@@ -443,9 +451,11 @@ class TestTensorRegisterHook(unittest.TestCase): ...@@ -443,9 +451,11 @@ class TestTensorRegisterHook(unittest.TestCase):
self.assertTrue(np.array_equal(y_grad, z)) self.assertTrue(np.array_equal(y_grad, z))
def test_multiple_hooks_for_interior_var(self): def test_multiple_hooks_for_interior_var(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
with _test_eager_guard(): with _test_eager_guard():
self.func_multiple_hooks_for_interior_var() self.func_multiple_hooks_for_interior_var()
self.func_multiple_hooks_for_interior_var() self.func_multiple_hooks_for_interior_var()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
def func_hook_in_double_grad(self): def func_hook_in_double_grad(self):
def double_print_hook(grad): def double_print_hook(grad):
......
python/paddle/fluid/tests/unittests/test_uniform_random_inplace_op.py
浏览文件 @ 4d3b7d7d
...@@ -158,6 +158,8 @@ class TestUniformRandomInplaceGrad(unittest.TestCase): ...@@ -158,6 +158,8 @@ class TestUniformRandomInplaceGrad(unittest.TestCase):
self.shape = (1000, 784) self.shape = (1000, 784)
def test_uniform_random_inplace_grad(self): def test_uniform_random_inplace_grad(self):
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
def test_grad(): def test_grad():
tensor_a = paddle.ones(self.shape) tensor_a = paddle.ones(self.shape)
tensor_a.stop_gradient = False tensor_a.stop_gradient = False
...@@ -174,6 +176,7 @@ class TestUniformRandomInplaceGrad(unittest.TestCase): ...@@ -174,6 +176,7 @@ class TestUniformRandomInplaceGrad(unittest.TestCase):
for place in places: for place in places:
paddle.set_device(place) paddle.set_device(place)
test_grad() test_grad()
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": False})
if __name__ == '__main__': if __name__ == '__main__':
......
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