diff --git a/paddle/phi/kernels/xpu/transpose_grad_kernel.cc b/paddle/phi/kernels/xpu/transpose_grad_kernel.cc index 9fce92b8262ab4c328096236eebcf159c795b9d3..2bd23ba2cdc15290d94fa0d3e284c9054efebe19 100644 --- a/paddle/phi/kernels/xpu/transpose_grad_kernel.cc +++ b/paddle/phi/kernels/xpu/transpose_grad_kernel.cc @@ -26,6 +26,14 @@ void TransposeGradKernel(const Context& dev_ctx, DenseTensor* x_grad) { using XPUType = typename XPUTypeTrait::Type; dev_ctx.template Alloc(x_grad); + if (x_grad->numel() == 0) { + return; + } + if (axis.size() == 0) { + phi::Copy(dev_ctx, out_grad, dev_ctx.GetPlace(), false, x_grad); + return; + } + std::vector reversed_axis(axis); for (size_t i = 0; i < axis.size(); i++) { reversed_axis[axis[i]] = i; diff --git a/python/paddle/fluid/tests/unittests/test_quantile_and_nanquantile.py b/python/paddle/fluid/tests/unittests/test_quantile_and_nanquantile.py index 1f5aaa6b0952b90210d28215b30e95436f7455a4..7d6d61e64c243dbdb980f786e99125158d37f05b 100644 --- a/python/paddle/fluid/tests/unittests/test_quantile_and_nanquantile.py +++ b/python/paddle/fluid/tests/unittests/test_quantile_and_nanquantile.py @@ -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): """ diff --git a/python/paddle/fluid/tests/unittests/test_zero_dim_tensor.py b/python/paddle/fluid/tests/unittests/test_zero_dim_tensor.py index 8fad691a455a785f640665f4274a701ce312172f..c0bf198fffa83982a4bc6faefe17de5367c5bd36 100644 --- a/python/paddle/fluid/tests/unittests/test_zero_dim_tensor.py +++ b/python/paddle/fluid/tests/unittests/test_zero_dim_tensor.py @@ -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,)) diff --git a/python/paddle/fluid/tests/unittests/xpu/test_zero_dim_tensor_xpu.py b/python/paddle/fluid/tests/unittests/xpu/test_zero_dim_tensor_xpu.py index 8d567bc420290c7e072569ed5a069a5316d8e250..43b44a07dcbb873cbab2ae6f3b959dd8c33c14ae 100644 --- a/python/paddle/fluid/tests/unittests/xpu/test_zero_dim_tensor_xpu.py +++ b/python/paddle/fluid/tests/unittests/xpu/test_zero_dim_tensor_xpu.py @@ -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') diff --git a/python/paddle/tensor/manipulation.py b/python/paddle/tensor/manipulation.py index 0c74a900e1b72af82096e800666c892a15a7f513..bdd903ee8f1966179301bccab04e3249b09ae299 100644 --- a/python/paddle/tensor/manipulation.py +++ b/python/paddle/tensor/manipulation.py @@ -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) diff --git a/python/paddle/tensor/stat.py b/python/paddle/tensor/stat.py index e152c2a366072de90d1d6ce09e32c60e71ebdda0..61a3fbffd72e3e533f12dc022a4e4bbb597a5d0e 100644 --- a/python/paddle/tensor/stat.py +++ b/python/paddle/tensor/stat.py @@ -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(