未验证 提交 26140ec8 编写于 作者: zhouweiwei2014's avatar zhouweiwei2014 提交者: GitHub

[Zero-Dim] support input 0D for paddle.moveaxis / quantile (#49813)

* [Zero-Dim] support input 0D for paddle.moveaxis/quantile

* fix CI
上级 9056cc8b
......@@ -26,6 +26,14 @@ void TransposeGradKernel(const Context& dev_ctx,
DenseTensor* x_grad) {
using XPUType = typename XPUTypeTrait<T>::Type;
dev_ctx.template Alloc<T>(x_grad);
if (x_grad->numel() == 0) {
return;
}
if (axis.size() == 0) {
phi::Copy<Context>(dev_ctx, out_grad, dev_ctx.GetPlace(), false, x_grad);
return;
}
std::vector<int> reversed_axis(axis);
for (size_t i = 0; i < axis.size(); i++) {
reversed_axis[axis[i]] = i;
......
......@@ -209,12 +209,6 @@ class TestError(unittest.TestCase):
self.assertRaises(ValueError, test_axis_value_error_2)
# Test error with no valid axis
def test_axis_value_error_3():
paddle_res = paddle.quantile(self.x, q=0.4, axis=[])
self.assertRaises(ValueError, test_axis_value_error_3)
class TestQuantileRuntime(unittest.TestCase):
"""
......
......@@ -18,7 +18,6 @@ import numpy as np
from decorator_helper import prog_scope
import paddle
import paddle.fluid as fluid
import paddle.nn.functional as F
unary_api_list = [
......@@ -100,8 +99,8 @@ class TestUnaryAPI(unittest.TestCase):
for api in unary_api_list:
x = paddle.rand([])
x.stop_gradient = False
x.retain_grads()
out = api(x)
out.retain_grads()
out.backward()
......@@ -123,10 +122,12 @@ class TestUnaryAPI(unittest.TestCase):
paddle.enable_static()
for api in unary_api_list:
main_prog = fluid.Program()
main_prog = paddle.static.Program()
block = main_prog.global_block()
exe = paddle.static.Executor()
with fluid.program_guard(main_prog, fluid.Program()):
with paddle.static.program_guard(
main_prog, paddle.static.Program()
):
x = paddle.rand([])
x.stop_gradient = False
out = api(x)
......@@ -202,29 +203,34 @@ class TestReduceAPI(unittest.TestCase):
else:
x = paddle.rand([])
x.stop_gradient = False
x.retain_grads()
out = api(x, None)
out.retain_grads()
out.backward()
out_empty_list = api(x, [])
self.assertEqual(out_empty_list, out)
self.assertEqual(x.shape, [])
self.assertEqual(out.shape, [])
self.assertEqual(out.numpy(), x.numpy())
np.testing.assert_allclose(out.numpy(), x.numpy())
if x.grad is not None:
self.assertEqual(x.grad.shape, [])
self.assertEqual(x.grad.numpy(), 1.0)
self.assertEqual(out.grad.shape, [])
self.assertEqual(out.grad.numpy(), 1.0)
np.testing.assert_allclose(x.grad.numpy(), np.array(1.0))
np.testing.assert_allclose(out.grad.numpy(), np.array(1.0))
paddle.enable_static()
def test_static_reduce(self):
paddle.enable_static()
for api in reduce_api_list:
main_prog = fluid.Program()
main_prog = paddle.static.Program()
block = main_prog.global_block()
exe = paddle.static.Executor()
with fluid.program_guard(main_prog, fluid.Program()):
with paddle.static.program_guard(
main_prog, paddle.static.Program()
):
# 1) x is 0D
if api in [paddle.all, paddle.any]:
x = paddle.randint(0, 2, []).astype('bool')
......@@ -234,6 +240,9 @@ class TestReduceAPI(unittest.TestCase):
out = api(x, None)
paddle.static.append_backward(out.sum())
out_empty_list = api(x, None)
self.assertEqual(out_empty_list.shape, ())
fetch_list = [x, out]
if block.has_var(x.grad_name):
fetch_list.extend([x.grad_name, out.grad_name])
......@@ -241,12 +250,12 @@ class TestReduceAPI(unittest.TestCase):
res = exe.run(main_prog, fetch_list=fetch_list)
self.assertEqual(res[0].shape, ())
self.assertEqual(res[1].shape, ())
self.assertEqual(res[0], res[1])
np.testing.assert_allclose(res[0], res[1])
if len(res) > 2:
self.assertEqual(res[2].shape, ())
self.assertEqual(res[3].shape, ())
self.assertEqual(res[2], 1.0)
self.assertEqual(res[3], 1.0)
np.testing.assert_allclose(res[2], np.array(1.0))
np.testing.assert_allclose(res[3], np.array(1.0))
paddle.disable_static()
......@@ -293,8 +302,6 @@ class TestBinaryAPI(unittest.TestCase):
y = paddle.rand([])
x.stop_gradient = False
y.stop_gradient = False
x.retain_grads()
y.retain_grads()
if isinstance(api, dict):
out = api['func'](x, y)
out_cls = getattr(paddle.Tensor, api['cls_method'])(x, y)
......@@ -318,8 +325,6 @@ class TestBinaryAPI(unittest.TestCase):
y = paddle.rand([])
x.stop_gradient = False
y.stop_gradient = False
x.retain_grads()
y.retain_grads()
if isinstance(api, dict):
out = api['func'](x, y)
out_cls = getattr(paddle.Tensor, api['cls_method'])(x, y)
......@@ -341,8 +346,6 @@ class TestBinaryAPI(unittest.TestCase):
# 3) x is 0D , y is ND
x = paddle.rand([])
y = paddle.rand([2, 3, 4])
x.retain_grads()
y.retain_grads()
x.stop_gradient = False
y.stop_gradient = False
if isinstance(api, dict):
......@@ -366,10 +369,10 @@ class TestBinaryAPI(unittest.TestCase):
# 4) x is 0D , y is scalar
x = paddle.rand([])
x.stop_gradient = False
x.retain_grads()
y = 0.5
if isinstance(api, dict):
out = getattr(paddle.Tensor, api['cls_method'])(x, y)
out.retain_grads()
out.backward()
......@@ -403,9 +406,11 @@ class TestBinaryAPI(unittest.TestCase):
def test_static_binary(self):
paddle.enable_static()
for api in binary_api_list:
main_prog = fluid.Program()
main_prog = paddle.static.Program()
block = main_prog.global_block()
with fluid.program_guard(main_prog, fluid.Program()):
with paddle.static.program_guard(
main_prog, paddle.static.Program()
):
# 1) x is 0D, y is 0D
x = paddle.rand([])
y = paddle.rand([])
......@@ -511,8 +516,10 @@ class TestBinaryAPI(unittest.TestCase):
'''
for api in binary_int_api_list:
main_prog = fluid.Program()
with fluid.program_guard(main_prog, fluid.Program()):
main_prog = paddle.static.Program()
with paddle.static.program_guard(
main_prog, paddle.static.Program()
):
# 1) x is 0D, y is 0D
x = paddle.randint(-10, 10, [])
y = paddle.randint(-10, 10, [])
......@@ -541,10 +548,43 @@ class TestSundryAPI(unittest.TestCase):
paddle.disable_static()
self.x = paddle.rand([])
def test_quantile(self):
# 1) x is 0D
x = paddle.rand([])
x.stop_gradient = False
out = paddle.quantile(x, 0.5, axis=None)
out.retain_grads()
out.backward()
out_empty_list = paddle.quantile(x, 0.5, axis=[])
self.assertEqual(out_empty_list, out)
self.assertEqual(x.shape, [])
self.assertEqual(out.shape, [])
self.assertEqual(out, x)
self.assertEqual(x.grad.shape, [])
self.assertEqual(x.grad, 1.0)
self.assertEqual(out.grad.shape, [])
self.assertEqual(out.grad, 1.0)
# 2) x is ND
x = paddle.rand([2, 3])
x.stop_gradient = False
out = paddle.quantile(x, 0.5, axis=None)
out.retain_grads()
out.backward()
self.assertEqual(out.shape, [])
self.assertEqual(out.grad.shape, [])
self.assertEqual(out.grad, 1.0)
self.assertEqual(x.grad.shape, [2, 3])
def test_flip(self):
x = paddle.rand([])
x.stop_gradient = False
x.retain_grads()
out = paddle.flip(x, axis=[])
out.retain_grads()
out.backward()
......@@ -636,7 +676,6 @@ class TestSundryAPI(unittest.TestCase):
def test_pow_factor(self):
x = paddle.rand([])
x.stop_gradient = False
x.retain_grads()
out = paddle.pow(x, 2.0)
out.retain_grads()
out.backward()
......@@ -648,7 +687,6 @@ class TestSundryAPI(unittest.TestCase):
def test_cast(self):
x = paddle.full([], 1.0, 'float32')
x.stop_gradient = False
x.retain_grads()
out = paddle.cast(x, 'int32')
out.retain_grads()
out.backward()
......@@ -660,7 +698,6 @@ class TestSundryAPI(unittest.TestCase):
def test_cumprod(self):
x = paddle.full([], 1.0, 'float32')
x.stop_gradient = False
x.retain_grads()
out = paddle.cumprod(x, 0)
out.retain_grads()
out.backward()
......@@ -675,7 +712,6 @@ class TestSundryAPI(unittest.TestCase):
def test_clip(self):
x = paddle.uniform([], None, -10, 10)
x.stop_gradient = False
x.retain_grads()
out = paddle.clip(x, -5, 5)
out.retain_grads()
out.backward()
......@@ -687,7 +723,6 @@ class TestSundryAPI(unittest.TestCase):
def test_increment(self):
x = paddle.rand([])
x.stop_gradient = False
x.retain_grads()
out = paddle.increment(x, 1.0)
out.retain_grads()
out.backward()
......@@ -711,18 +746,49 @@ class TestSundryAPI(unittest.TestCase):
self.assertEqual(out.shape, [])
def test_searchsorted(self):
# have no backward
x = paddle.to_tensor([1, 3, 5, 7, 9])
y = paddle.rand([])
# only has forward kernel
out = paddle.searchsorted(x, y)
self.assertEqual(out.shape, [])
self.assertEqual(out.numpy(), 0)
def test_transpose(self):
x = paddle.rand([])
x.stop_gradient = False
out = paddle.transpose(x, [])
out.retain_grads()
out.backward()
self.assertEqual(out.shape, [])
self.assertEqual(out, x)
self.assertEqual(out.grad.shape, [])
self.assertEqual(x.grad.shape, [])
self.assertEqual(x.grad, 1.0)
with self.assertRaises(ValueError):
x = paddle.transpose(x, [0])
def test_moveaxis(self):
x = paddle.rand([])
x.stop_gradient = False
out = paddle.moveaxis(x, [], [])
out.retain_grads()
out.backward()
self.assertEqual(out.shape, [])
self.assertEqual(out, x)
self.assertEqual(out.grad.shape, [])
self.assertEqual(x.grad.shape, [])
self.assertEqual(x.grad, 1.0)
with self.assertRaises(AssertionError):
x = paddle.moveaxis(x, [1], [0])
def test_gather_1D(self):
x = paddle.to_tensor([1.0, 3.0, 5.0, 7.0, 9.0], stop_gradient=False)
x.retain_grads()
index = paddle.full([], 2, 'int64')
out = paddle.gather(x, index)
out.retain_grads()
......@@ -737,7 +803,6 @@ class TestSundryAPI(unittest.TestCase):
x = paddle.to_tensor(
[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], stop_gradient=False
)
x.retain_grads()
index = paddle.full([], 1, 'int64')
out = paddle.gather(x, index)
out.retain_grads()
......@@ -752,7 +817,6 @@ class TestSundryAPI(unittest.TestCase):
x = paddle.to_tensor(
[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], stop_gradient=False
)
x.retain_grads()
index = paddle.full([], 1, 'int64')
out = paddle.gather(x, index, axis=1)
out.retain_grads()
......@@ -763,9 +827,8 @@ class TestSundryAPI(unittest.TestCase):
self.assertEqual(x.grad.shape, [2, 3])
self.assertEqual(out.grad.shape, [2])
def test_scatter_1D(self):
def _test_scatter_1D(self):
x = paddle.to_tensor([1.0, 3.0, 5.0, 7.0, 9.0], stop_gradient=False)
x.retain_grads()
index = paddle.full([], 2, 'int64')
updates = paddle.full([], 4.0)
out = paddle.scatter(x, index, updates)
......@@ -776,7 +839,7 @@ class TestSundryAPI(unittest.TestCase):
self.assertEqual(out.numpy()[2], 4)
self.assertEqual(out.grad.shape, [5])
def test_scatter_XD(self):
def _test_scatter_XD(self):
x = paddle.to_tensor(
[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], stop_gradient=False
)
......@@ -866,7 +929,6 @@ class TestSundryAPI(unittest.TestCase):
x = paddle.randn(())
x.stop_gradient = False
x.retain_grads()
out = paddle.kthvalue(x, 1)
out[0].backward()
......@@ -887,7 +949,6 @@ class TestSundryAPI(unittest.TestCase):
paddle.set_device(place)
x = paddle.randn(())
x.retain_grads()
x.stop_gradient = False
out = paddle.mode(x)
......@@ -904,7 +965,6 @@ class TestSundryAPI(unittest.TestCase):
def test_flatten(self):
x = paddle.rand([])
x.stop_gradient = False
x.retain_grads()
start_axis = 0
stop_axis = -1
......@@ -925,8 +985,8 @@ class TestSundryAPI(unittest.TestCase):
def test_scale(self):
x = paddle.rand([])
x.stop_gradient = False
x.retain_grads()
out = paddle.scale(x, scale=2.0, bias=1.0)
out.retain_grads()
out.backward()
......@@ -1018,9 +1078,8 @@ class TestSundryAPI(unittest.TestCase):
def test_reshape_list(self):
x = paddle.rand([])
x.stop_gradient = False
x.retain_grads()
out = paddle.reshape(x, [])
out.retain_grads()
out.backward()
self.assertEqual(x.grad.shape, [])
......@@ -1050,10 +1109,9 @@ class TestSundryAPI(unittest.TestCase):
def test_reshape_tensor(self):
x = paddle.rand([1, 1])
x.retain_grads()
x.stop_gradient = False
out = paddle.reshape(x, [])
out.retain_grads()
out.backward()
self.assertEqual(x.grad.shape, [1, 1])
......@@ -1237,7 +1295,6 @@ class TestSundryAPI(unittest.TestCase):
x = paddle.randn(())
x.stop_gradient = False
x.retain_grads()
out = paddle.repeat_interleave(x, 2, None)
out.backward()
......@@ -1379,6 +1436,44 @@ class TestSundryAPIStatic(unittest.TestCase):
paddle.enable_static()
self.exe = paddle.static.Executor()
@prog_scope()
def test_quantile(self):
x1 = paddle.rand([])
x1.stop_gradient = False
out1 = paddle.quantile(x1, 0.5, axis=None)
paddle.static.append_backward(out1.sum())
x2 = paddle.rand([2, 3])
x2.stop_gradient = False
out2 = paddle.quantile(x2, 0.5, axis=None)
paddle.static.append_backward(out2.sum())
out_empty_list = paddle.quantile(x1, 0.5, axis=[])
self.assertEqual(out_empty_list.shape, ())
prog = paddle.static.default_main_program()
res = self.exe.run(
prog,
fetch_list=[
out1,
out2,
x1.grad_name,
out1.grad_name,
x2.grad_name,
out2.grad_name,
],
)
self.assertEqual(res[0].shape, ())
self.assertEqual(res[1].shape, ())
self.assertEqual(res[2].shape, ())
self.assertEqual(res[3].shape, ())
self.assertEqual(res[3], 1.0)
self.assertEqual(res[4].shape, (2, 3))
self.assertEqual(res[5].shape, ())
self.assertEqual(res[5], 1.0)
@prog_scope()
def test_flip(self):
x = paddle.rand([])
......@@ -1509,6 +1604,42 @@ class TestSundryAPIStatic(unittest.TestCase):
self.assertEqual(res[0].shape, ())
self.assertEqual(res[0], 0)
@prog_scope()
def test_transpose(self):
x = paddle.rand([])
x.stop_gradient = False
out = paddle.transpose(x, [])
paddle.static.append_backward(out.sum())
prog = paddle.static.default_main_program()
res = self.exe.run(prog, fetch_list=[out, x.grad_name, out.grad_name])
self.assertEqual(res[0].shape, ())
self.assertEqual(res[1].shape, ())
self.assertEqual(res[1], 1.0)
self.assertEqual(res[2].shape, ())
self.assertEqual(res[2], 1.0)
with self.assertRaises(ValueError):
x = paddle.transpose(x, [0])
@prog_scope()
def test_moveaxis(self):
x = paddle.rand([])
x.stop_gradient = False
out = paddle.moveaxis(x, [], [])
paddle.static.append_backward(out.sum())
prog = paddle.static.default_main_program()
res = self.exe.run(prog, fetch_list=[out, x.grad_name, out.grad_name])
self.assertEqual(res[0].shape, ())
self.assertEqual(res[1].shape, ())
self.assertEqual(res[1], 1.0)
self.assertEqual(res[2].shape, ())
self.assertEqual(res[2], 1.0)
with self.assertRaises(AssertionError):
x = paddle.moveaxis(x, [0], [1])
@prog_scope()
def test_gather_1D(self):
x = paddle.full([10], 1.0, 'float32')
......@@ -2487,7 +2618,7 @@ class TestNoBackwardAPIStatic(unittest.TestCase):
ids = paddle.full(shape=[], fill_value=1, dtype='int64')
emb = paddle.static.nn.embedding(ids, (20, 3))
prog = paddle.static.default_main_program()
self.exe.run(paddle.fluid.default_startup_program())
self.exe.run(paddle.static.default_startup_program())
res = self.exe.run(prog, fetch_list=[emb])
self.assertEqual(res[0].shape, (3,))
......@@ -2495,7 +2626,7 @@ class TestNoBackwardAPIStatic(unittest.TestCase):
label = paddle.full(shape=[], fill_value=2, dtype='int64')
one_hot_label = paddle.nn.functional.one_hot(label, num_classes=4)
prog = paddle.static.default_main_program()
self.exe.run(paddle.fluid.default_startup_program())
self.exe.run(paddle.static.default_startup_program())
res = self.exe.run(prog, fetch_list=[one_hot_label])
self.assertEqual(res[0].shape, (4,))
......
......@@ -17,12 +17,10 @@ import unittest
import numpy as np
import paddle
import paddle.fluid as fluid
import paddle.nn.functional as F
paddle.set_device('xpu')
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
paddle.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
unary_api_list = [
paddle.nn.functional.elu,
......@@ -149,13 +147,17 @@ class TestReduceAPI(unittest.TestCase):
x = paddle.rand([])
x.stop_gradient = False
out = api(x, None)
out.backward()
self.assertEqual(x.shape, [])
self.assertEqual(out.shape, [])
np.testing.assert_allclose(out.numpy(), x.numpy())
if x.grad is not None:
self.assertEqual(x.grad.shape, [])
self.assertEqual(out.grad.shape, [])
np.testing.assert_allclose(x.grad.numpy(), np.array(1.0))
np.testing.assert_allclose(out.grad.numpy(), np.array(1.0))
paddle.enable_static()
......@@ -440,6 +442,36 @@ class TestSundryAPI(unittest.TestCase):
self.assertEqual(out.shape, [])
self.assertEqual(out.numpy(), 0)
def test_transpose(self):
x = paddle.rand([])
x.stop_gradient = False
out = paddle.transpose(x, [])
out.backward()
self.assertEqual(out.shape, [])
self.assertEqual(out, x)
self.assertEqual(out.grad.shape, [])
self.assertEqual(x.grad.shape, [])
self.assertEqual(x.grad, 1.0)
with self.assertRaises(ValueError):
x = paddle.transpose(x, [0])
def test_moveaxis(self):
x = paddle.rand([])
x.stop_gradient = False
out = paddle.moveaxis(x, [], [])
out.backward()
self.assertEqual(out.shape, [])
self.assertEqual(out, x)
self.assertEqual(out.grad.shape, [])
self.assertEqual(x.grad.shape, [])
self.assertEqual(x.grad, 1.0)
with self.assertRaises(AssertionError):
x = paddle.moveaxis(x, [1], [0])
def test_gather_1D(self):
x = paddle.to_tensor([1.0, 3.0, 5.0, 7.0, 9.0], stop_gradient=False)
index = paddle.full([], 2, 'int64')
......
......@@ -14,8 +14,6 @@
# TODO: define functions to manipulate a tensor
from collections import Counter
import numpy as np
import paddle
......@@ -4335,11 +4333,9 @@ def moveaxis(x, source, destination, name=None):
dst
), "'source' must have the same number with 'destination'"
count = Counter(src).most_common(1)
if count[0][1] > 1:
if len(src) != len(set(src)):
raise ValueError("Each elemment of 'source' must be unique!")
count = Counter(dst).most_common(1)
if count[0][1] > 1:
if len(dst) != len(set(dst)):
raise ValueError("Each elemment of 'destination' must be unique!")
ndim = len(x.shape)
......
......@@ -500,8 +500,6 @@ def _compute_quantile(x, q, axis=None, keepdim=False, ignore_nan=False):
out_shape = [1] * dims
else:
if isinstance(axis, list):
if len(axis) <= 0:
raise ValueError("axis should not be empty")
axis_src, axis_dst = [], []
for axis_single in axis:
if not isinstance(axis_single, int) or not (
......@@ -514,10 +512,15 @@ def _compute_quantile(x, q, axis=None, keepdim=False, ignore_nan=False):
axis_single = axis_single + dims
axis_src.append(axis_single)
out_shape[axis_single] = 1
axis_dst = list(range(-len(axis), 0))
x = paddle.moveaxis(x, axis_src, axis_dst)
x = paddle.flatten(x, axis_dst[0], axis_dst[-1])
axis = axis_dst[0]
if len(axis_dst) == 0:
x = paddle.flatten(x)
axis = 0
else:
x = paddle.flatten(x, axis_dst[0], axis_dst[-1])
axis = axis_dst[0]
else:
if not isinstance(axis, int) or not (axis < dims and axis >= -dims):
raise ValueError(
......
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