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Update the demo of paddle.grad (#26498)
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* update the demo codes of paddle.grad.
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wzzju authored Aug 22, 2020
1 parent c11c83f commit c037d62
Showing 1 changed file with 37 additions and 38 deletions.
75 changes: 37 additions & 38 deletions python/paddle/fluid/dygraph/base.py
Original file line number Diff line number Diff line change
Expand Up @@ -375,47 +375,46 @@ def grad(outputs,
Examples 1:
.. code-block:: python
import paddle.fluid as fluid
import paddle
paddle.disable_static()
def test_dygraph_grad(create_graph):
with fluid.dygraph.guard():
x = fluid.layers.ones(shape=[1], dtype='float32')
x.stop_gradient = False
y = x * x
# Since y = x * x, dx = 2 * x
dx = fluid.dygraph.grad(
outputs=[y],
inputs=[x],
create_graph=create_graph,
retain_graph=True)[0]
z = y + dx
# If create_graph = False, the gradient of dx
# would not be backpropagated. Therefore,
# z = x * x + dx, and x.gradient() = 2 * x = 2.0
# If create_graph = True, the gradient of dx
# would be backpropagated. Therefore,
# z = x * x + dx = x * x + 2 * x, and
# x.gradient() = 2 * x + 2 = 4.0
z.backward()
return x.gradient()
print(test_dygraph_grad(create_graph=False)) # [2.]
x = paddle.ones(shape=[1], dtype='float32')
x.stop_gradient = False
y = x * x
# Since y = x * x, dx = 2 * x
dx = paddle.grad(
outputs=[y],
inputs=[x],
create_graph=create_graph,
retain_graph=True)[0]
z = y + dx
# If create_graph = False, the gradient of dx
# would not be backpropagated. Therefore,
# z = x * x + dx, and x.gradient() = 2 * x = 2.0
# If create_graph = True, the gradient of dx
# would be backpropagated. Therefore,
# z = x * x + dx = x * x + 2 * x, and
# x.gradient() = 2 * x + 2 = 4.0
z.backward()
return x.gradient()
print(test_dygraph_grad(create_graph=False)) # [2.]
print(test_dygraph_grad(create_graph=True)) # [4.]
Examples 2:
.. code-block:: python
import paddle.fluid as fluid
fluid.enable_dygraph()
import paddle
paddle.disable_static()
def test_dygraph_grad(grad_outputs=None):
x = fluid.layers.fill_constant(shape=[1], value=2.0, dtype='float32')
x = paddle.fill_constant(shape=[1], value=2.0, dtype='float32')
x.stop_gradient = False
y1 = x * x
Expand All @@ -431,27 +430,27 @@ def test_dygraph_grad(grad_outputs=None):
# Therefore, the final result would be:
# dx = 2 * x * dy1 + 3 * dy2 = 4 * dy1 + 3 * dy2.
dx = fluid.dygraph.grad(
dx = paddle.grad(
outputs=[y1, y2],
inputs=[x],
grad_outputs=grad_outputs)[0]
return dx.numpy()
THREE = fluid.layers.fill_constant(shape=[1], value=3.0, dtype='float32')
FOUR = fluid.layers.fill_constant(shape=[1], value=4.0, dtype='float32')
grad_value = paddle.fill_constant(shape=[1], value=4.0, dtype='float32')
# dy1 = [1], dy2 = [1]
print(test_dygraph_grad(None)) # [7.]
# dy1 = [1], dy2 = [4]
print(test_dygraph_grad([None, FOUR])) # [16.]
print(test_dygraph_grad([None, grad_value])) # [16.]
# dy1 = [4], dy2 = [1]
print(test_dygraph_grad([FOUR, None])) # [19.]
print(test_dygraph_grad([grad_value, None])) # [19.]
# dy1 = [3], dy2 = [4]
print(test_dygraph_grad([THREE, FOUR])) # [24.]
grad_y1 = paddle.fill_constant(shape=[1], value=3.0, dtype='float32')
print(test_dygraph_grad([grad_y1, grad_value])) # [24.]
'''

def check_in_out(in_out_list, name):
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