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[Zero-Dim] reshape/reshape_/reverse 0D support #49357

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merged 7 commits into from
Jan 3, 2023
Merged

[Zero-Dim] reshape/reshape_/reverse 0D support #49357

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d595f29
[Zero-Dim] reshape/reshape_/reverse 0D support
Dec 27, 2022
da40042
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
Dec 27, 2022
130dd5c
rm comment
Dec 27, 2022
9240a64
change paddle.to_tensor to paddle.full
Dec 27, 2022
72498fb
fix docs
Dec 28, 2022
df63aee
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
Dec 29, 2022
fa3e474
update paddle.full
Dec 29, 2022
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5 changes: 0 additions & 5 deletions paddle/fluid/operators/reshape_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -114,11 +114,6 @@ class ReshapeOp : public framework::OperatorWithKernel {
return;
}

PADDLE_ENFORCE_EQ(!shape.empty(),
true,
platform::errors::InvalidArgument(
"The parameter 'shape' in ReshapeOp must be set. "
"But received 'shape' is empty."));
auto x_dims = ctx->GetInputDim("X");
auto out_dims = ValidateShape(shape, x_dims);
ctx->SetOutputDim("Out", out_dims);
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3 changes: 3 additions & 0 deletions paddle/phi/kernels/gpu/flip_kernel.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -101,6 +101,9 @@ void FlipKernel(const Context& dev_ctx,
DenseTensor* out) {
const size_t total_dims = x.dims().size();
switch (total_dims) {
case 0:
LaunchFlipCudaKernel<T, Context, 0>(dev_ctx, x, axis, out);
break;
case 1:
LaunchFlipCudaKernel<T, Context, 1>(dev_ctx, x, axis, out);
break;
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6 changes: 3 additions & 3 deletions python/paddle/fluid/tests/unittests/test_reshape_op.py
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Expand Up @@ -49,20 +49,20 @@ def test_check_grad(self):
class TestReshapeOp_ZeroDim1(OpTest):
def init_data(self):
self.ori_shape = ()
self.new_shape = 1
self.new_shape = (1,)
self.infered_shape = 1


class TestReshapeOp_ZeroDim2(OpTest):
def init_data(self):
self.ori_shape = ()
self.new_shape = -1
self.new_shape = (-1,)
self.infered_shape = 1


class TestReshapeOp_ZeroDim3(OpTest):
def init_data(self):
self.ori_shape = 1
self.ori_shape = (1,)
self.new_shape = ()
self.infered_shape = ()

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171 changes: 171 additions & 0 deletions python/paddle/fluid/tests/unittests/test_zero_dim_tensor.py
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Expand Up @@ -712,6 +712,105 @@ def test_scatter_nd(self):
self.assertEqual(out.numpy()[3], 2)
self.assertEqual(out.grad.shape, [5])

def test_reshape_list(self):
x = paddle.rand([])
x.stop_gradient = False

out = paddle.reshape(x, [])
out.backward()
self.assertEqual(x.grad.shape, [])
self.assertEqual(out.shape, [])
self.assertEqual(out.grad.shape, [])

out = paddle.reshape(x, [1])
out.backward()
self.assertEqual(x.grad.shape, [])
self.assertEqual(out.shape, [1])
self.assertEqual(out.grad.shape, [1])

out = paddle.reshape(x, [-1])
out.backward()
self.assertEqual(x.grad.shape, [])
self.assertEqual(out.shape, [1])
self.assertEqual(out.grad.shape, [1])

out = paddle.reshape(x, [-1, 1])
out.backward()
self.assertEqual(x.grad.shape, [])
self.assertEqual(out.shape, [1, 1])
self.assertEqual(out.grad.shape, [1, 1])

def test_reshape_tensor(self):
x = paddle.rand([1, 1])
x.stop_gradient = False

out = paddle.reshape(x, [])
out.backward()
self.assertEqual(x.grad.shape, [1, 1])
self.assertEqual(out.shape, [])
self.assertEqual(out.grad.shape, [])

new_shape = paddle.to_tensor((1,))
out = paddle.reshape(x, new_shape)
out.backward()
self.assertEqual(x.grad.shape, [1, 1])
self.assertEqual(out.shape, [1])
self.assertEqual(out.grad.shape, [1])

new_shape = paddle.to_tensor((-1,))
out = paddle.reshape(x, new_shape)
out.backward()
self.assertEqual(x.grad.shape, [1, 1])
self.assertEqual(out.shape, [1])
self.assertEqual(out.grad.shape, [1])

new_shape = [paddle.to_tensor(-1), paddle.to_tensor(1)]
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目前paddle.to_tensor还有些bug，会把0D强转为1D，可以把这个改成paddle.full([], -1) paddle.full([], 1)

然后API文档这里用 形状为[]的0D Tensor 比较好
infoflow 2022-12-27 14-44-38

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Done.

out = paddle.reshape(x, new_shape)
out.backward()
self.assertEqual(x.grad.shape, [1, 1])
self.assertEqual(out.shape, [1, 1])
self.assertEqual(out.grad.shape, [1, 1])

def test_reshape__list(self):
x = paddle.rand([])
out = paddle.reshape_(x, [])
self.assertEqual(out.shape, [])

out = paddle.reshape_(x, [1])
self.assertEqual(out.shape, [1])

out = paddle.reshape_(x, [-1])
self.assertEqual(out.shape, [1])

out = paddle.reshape_(x, [-1, 1])
self.assertEqual(out.shape, [1, 1])

def test_reshape__tensor(self):
x = paddle.rand([1, 1])
out = paddle.reshape_(x, [])
self.assertEqual(out.shape, [])

new_shape = paddle.to_tensor((1,))
out = paddle.reshape_(x, new_shape)
self.assertEqual(out.shape, [1])

new_shape = paddle.to_tensor((-1,))
out = paddle.reshape_(x, new_shape)
self.assertEqual(out.shape, [1])

new_shape = [paddle.to_tensor(-1), paddle.to_tensor(1)]
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out = paddle.reshape_(x, new_shape)
self.assertEqual(out.shape, [1, 1])

def test_reverse(self):
x = paddle.rand([])
x.stop_gradient = False
out = paddle.reverse(x, axis=[])
out.backward()
self.assertEqual(x.shape, [])
self.assertEqual(out.shape, [])
self.assertEqual(out.grad.shape, [])


class TestSundryAPIStatic(unittest.TestCase):
def setUp(self):
Expand Down Expand Up @@ -914,6 +1013,78 @@ def test_scatter_nd(self):
self.assertEqual(res[0].shape, (5,))
self.assertEqual(res[0][3], 2)

@prog_scope()
def test_reshape_list(self):
x1 = paddle.rand([])
x2 = paddle.rand([])
x3 = paddle.rand([])
x4 = paddle.rand([])
x1.stop_gradient = False
x2.stop_gradient = False
x3.stop_gradient = False
x4.stop_gradient = False

out1 = paddle.reshape(x1, [])
paddle.static.append_backward(out1)

out2 = paddle.reshape(x2, [1])
paddle.static.append_backward(out2)

out3 = paddle.reshape(x3, [-1])
paddle.static.append_backward(out3)

out4 = paddle.reshape(x4, [-1, 1])
paddle.static.append_backward(out4)

program = paddle.static.default_main_program()
res1, res2, res3, res4 = self.exe.run(
program, fetch_list=[out1, out2, out3, out4]
)
self.assertEqual(res1.shape, ())
self.assertEqual(res2.shape, (1,))
self.assertEqual(res3.shape, (1,))
self.assertEqual(res4.shape, (1, 1))

@prog_scope()
def test_reshape_tensor(self):
x1 = paddle.rand([])
x2 = paddle.rand([])
x3 = paddle.rand([])
x1.stop_gradient = False
x2.stop_gradient = False
x3.stop_gradient = False

new_shape = paddle.to_tensor((1,))
out1 = paddle.reshape(x1, new_shape)
paddle.static.append_backward(out1)

new_shape = paddle.to_tensor((-1,))
out2 = paddle.reshape(x2, new_shape)
paddle.static.append_backward(out2)

new_shape = [paddle.to_tensor(-1), paddle.to_tensor(1)]
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out3 = paddle.reshape(x3, new_shape)
paddle.static.append_backward(out3)

program = paddle.static.default_main_program()
res1, res2, res3 = self.exe.run(program, fetch_list=[out1, out2, out3])
self.assertEqual(res1.shape, (1,))
self.assertEqual(res2.shape, (1,))
self.assertEqual(res3.shape, (1, 1))

@prog_scope()
def test_reverse(self):
x = paddle.rand([])
x.stop_gradient = False

out = paddle.reverse(x, axis=[])
paddle.static.append_backward(out)

program = paddle.static.default_main_program()
res1, res2 = self.exe.run(program, fetch_list=[x, out])
self.assertEqual(res1.shape, ())
self.assertEqual(res2.shape, ())


# Use to test API whose zero-dim input tensors don't have grad and not need to test backward in OpTest.
class TestNoBackwardAPI(unittest.TestCase):
Expand Down
99 changes: 99 additions & 0 deletions python/paddle/fluid/tests/unittests/xpu/test_zero_dim_tensor_xpu.py
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Expand Up @@ -521,6 +521,105 @@ def test_scatter__XD(self):
for i in range(3):
self.assertEqual(out.numpy()[1][i], updates.numpy()[i])

def test_reshape_list(self):
x = paddle.rand([])
x.stop_gradient = False

out = paddle.reshape(x, [])
out.backward()
self.assertEqual(x.grad.shape, [])
self.assertEqual(out.shape, [])
self.assertEqual(out.grad.shape, [])

out = paddle.reshape(x, [1])
out.backward()
self.assertEqual(x.grad.shape, [])
self.assertEqual(out.shape, [1])
self.assertEqual(out.grad.shape, [1])

out = paddle.reshape(x, [-1])
out.backward()
self.assertEqual(x.grad.shape, [])
self.assertEqual(out.shape, [1])
self.assertEqual(out.grad.shape, [1])

out = paddle.reshape(x, [-1, 1])
out.backward()
self.assertEqual(x.grad.shape, [])
self.assertEqual(out.shape, [1, 1])
self.assertEqual(out.grad.shape, [1, 1])

def test_reshape_tensor(self):
x = paddle.rand([1, 1])
x.stop_gradient = False

out = paddle.reshape(x, [])
out.backward()
self.assertEqual(x.grad.shape, [1, 1])
self.assertEqual(out.shape, [])
self.assertEqual(out.grad.shape, [])

new_shape = paddle.to_tensor((1,))
out = paddle.reshape(x, new_shape)
out.backward()
self.assertEqual(x.grad.shape, [1, 1])
self.assertEqual(out.shape, [1])
self.assertEqual(out.grad.shape, [1])

new_shape = paddle.to_tensor((-1,))
out = paddle.reshape(x, new_shape)
out.backward()
self.assertEqual(x.grad.shape, [1, 1])
self.assertEqual(out.shape, [1])
self.assertEqual(out.grad.shape, [1])

new_shape = [paddle.to_tensor(-1), paddle.to_tensor(1)]
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out = paddle.reshape(x, new_shape)
out.backward()
self.assertEqual(x.grad.shape, [1, 1])
self.assertEqual(out.shape, [1, 1])
self.assertEqual(out.grad.shape, [1, 1])

def test_reshape__list(self):
x = paddle.rand([])
out = paddle.reshape_(x, [])
self.assertEqual(out.shape, [])

out = paddle.reshape_(x, [1])
self.assertEqual(out.shape, [1])

out = paddle.reshape_(x, [-1])
self.assertEqual(out.shape, [1])

out = paddle.reshape_(x, [-1, 1])
self.assertEqual(out.shape, [1, 1])

def test_reshape__tensor(self):
x = paddle.rand([1, 1])
out = paddle.reshape_(x, [])
self.assertEqual(out.shape, [])

new_shape = paddle.to_tensor((1,))
out = paddle.reshape_(x, new_shape)
self.assertEqual(out.shape, [1])

new_shape = paddle.to_tensor((-1,))
out = paddle.reshape_(x, new_shape)
self.assertEqual(out.shape, [1])

new_shape = [paddle.to_tensor(-1), paddle.to_tensor(1)]
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out = paddle.reshape_(x, new_shape)
self.assertEqual(out.shape, [1, 1])

def test_reverse(self):
x = paddle.rand([])
x.stop_gradient = False
out = paddle.reverse(x, axis=[])
out.backward()
self.assertEqual(x.shape, [])
self.assertEqual(out.shape, [])
self.assertEqual(out.grad.shape, [])


# Use to test API whose zero-dim input tensors don't have grad and not need to test backward in OpTest.
class TestNoBackwardAPI(unittest.TestCase):
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4 changes: 0 additions & 4 deletions python/paddle/tensor/manipulation.py
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Expand Up @@ -3574,10 +3574,6 @@ def get_attr_shape(list_shape):
shape.stop_gradient = True
inputs["Shape"] = shape
elif isinstance(shape, (list, tuple)):
assert len(shape) > 0, (
"The size of 'shape' in reshape can't be zero, "
"but received %s." % len(shape)
)
attrs["shape"] = get_attr_shape(shape)
if utils._contain_var(shape):
inputs['ShapeTensor'] = utils._convert_to_tensor_list(shape)
Expand Down