From 5f3c7ba437f020b32ef53e6916b8264d7a9ed830 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E5=BC=A0=E6=98=A5=E4=B9=94?= <83450930+Liyulingyue@users.noreply.github.com> Date: Wed, 30 Aug 2023 16:15:24 +0800 Subject: [PATCH] [xdoctest] reformat example code with google style in No. 201 (#56472) * xdoc * Update python/paddle/tensor/einsum.py * Update einsum.py * Apply suggestions from code review * Update einsum.py * Apply suggestions from code review --- python/paddle/tensor/einsum.py | 130 ++++++++++++++++----------------- 1 file changed, 63 insertions(+), 67 deletions(-) diff --git a/python/paddle/tensor/einsum.py b/python/paddle/tensor/einsum.py index c379136e26287..11fb7e6f47607 100644 --- a/python/paddle/tensor/einsum.py +++ b/python/paddle/tensor/einsum.py @@ -953,73 +953,69 @@ def einsum(equation, *operands): Examples: .. code-block:: python - import paddle - paddle.seed(102) - x = paddle.rand([4]) - y = paddle.rand([5]) - - # sum - print(paddle.einsum('i->', x)) - # Tensor(shape=[], dtype=float32, place=CUDAPlace(0), stop_gradient=True, - # 1.95791852) - - # dot - print(paddle.einsum('i,i->', x, x)) - # Tensor(shape=[], dtype=float32, place=CUDAPlace(0), stop_gradient=True, - # 1.45936954) - - # outer - print(paddle.einsum("i,j->ij", x, y)) - # Tensor(shape=[4, 5], dtype=float32, place=CUDAPlace(0), stop_gradient=True, - # [[0.00079869, 0.00120950, 0.00136844, 0.00187187, 0.00192194], - # [0.23455200, 0.35519385, 0.40186870, 0.54970956, 0.56441545], - # [0.11773264, 0.17828843, 0.20171674, 0.27592498, 0.28330654], - # [0.32897076, 0.49817693, 0.56364071, 0.77099484, 0.79162055]]) - - A = paddle.rand([2, 3, 2]) - B = paddle.rand([2, 2, 3]) - - # transpose - print(paddle.einsum('ijk->kji', A)) - # Tensor(shape=[2, 3, 2], dtype=float32, place=CUDAPlace(0), stop_gradient=True, - # [[[0.95649719, 0.49684682], - # [0.80071914, 0.46258664], - # [0.49814570, 0.33383518]], - # - # [[0.07637714, 0.29374704], - # [0.51470858, 0.51907635], - # [0.99066722, 0.55802226]]]) - - # batch matrix multiplication - print(paddle.einsum('ijk, ikl->ijl', A,B)) - # Tensor(shape=[2, 3, 3], dtype=float32, place=CUDAPlace(0), stop_gradient=True, - # [[[0.32172769, 0.50617385, 0.41394392], - # [0.51736701, 0.49921003, 0.38730967], - # [0.69078457, 0.42282537, 0.30161136]], - # - # [[0.32043904, 0.18164253, 0.27810261], - # [0.50226176, 0.24512935, 0.39881429], - # [0.51476848, 0.23367381, 0.39229113]]]) - - # Ellipsis transpose - print(paddle.einsum('...jk->...kj', A)) - # Tensor(shape=[2, 2, 3], dtype=float32, place=CUDAPlace(0), stop_gradient=True, - # [[[0.95649719, 0.80071914, 0.49814570], - # [0.07637714, 0.51470858, 0.99066722]], - # - # [[0.49684682, 0.46258664, 0.33383518], - # [0.29374704, 0.51907635, 0.55802226]]]) - - # Ellipsis batch matrix multiplication - print(paddle.einsum('...jk, ...kl->...jl', A,B)) - # Tensor(shape=[2, 3, 3], dtype=float32, place=CUDAPlace(0), stop_gradient=True, - # [[[0.32172769, 0.50617385, 0.41394392], - # [0.51736701, 0.49921003, 0.38730967], - # [0.69078457, 0.42282537, 0.30161136]], - # - # [[0.32043904, 0.18164253, 0.27810261], - # [0.50226176, 0.24512935, 0.39881429], - # [0.51476848, 0.23367381, 0.39229113]]]) + >>> import paddle + >>> paddle.seed(102) + >>> x = paddle.rand([4]) + >>> y = paddle.rand([5]) + + >>> # sum + >>> print(paddle.einsum('i->', x)) + Tensor(shape=[], dtype=float32, place=Place(cpu), stop_gradient=True, + 1.81225157) + + >>> # dot + >>> print(paddle.einsum('i,i->', x, x)) + Tensor(shape=[], dtype=float32, place=Place(cpu), stop_gradient=True, + 1.13530672) + + >>> # outer + >>> print(paddle.einsum("i,j->ij", x, y)) + Tensor(shape=[4, 5], dtype=float32, place=Place(cpu), stop_gradient=True, + [[0.26443148, 0.05962684, 0.25360870, 0.21900642, 0.56994802], + [0.20955276, 0.04725220, 0.20097610, 0.17355499, 0.45166403], + [0.35836059, 0.08080698, 0.34369346, 0.29680005, 0.77240014], + [0.00484230, 0.00109189, 0.00464411, 0.00401047, 0.01043695]]) + + >>> A = paddle.rand([2, 3, 2]) + >>> B = paddle.rand([2, 2, 3]) + + >>> # transpose + >>> print(paddle.einsum('ijk->kji', A)) + Tensor(shape=[2, 3, 2], dtype=float32, place=Place(cpu), stop_gradient=True, + [[[0.50882483, 0.56067896], + [0.84598064, 0.36310029], + [0.55289471, 0.33273944]], + [[0.04836850, 0.73811269], + [0.29769155, 0.28137168], + [0.84636718, 0.67521429]]]) + + >>> # batch matrix multiplication + >>> print(paddle.einsum('ijk, ikl->ijl', A,B)) + Tensor(shape=[2, 3, 3], dtype=float32, place=Place(cpu), stop_gradient=True, + [[[0.36321065, 0.42009076, 0.40849245], + [0.74353045, 0.79189068, 0.81345987], + [0.90488225, 0.79786193, 0.93451476]], + [[0.12680580, 1.06945944, 0.79821426], + [0.07774551, 0.55068684, 0.44512171], + [0.08053084, 0.80583858, 0.56031936]]]) + + >>> # Ellipsis transpose + >>> print(paddle.einsum('...jk->...kj', A)) + Tensor(shape=[2, 2, 3], dtype=float32, place=Place(cpu), stop_gradient=True, + [[[0.50882483, 0.84598064, 0.55289471], + [0.04836850, 0.29769155, 0.84636718]], + [[0.56067896, 0.36310029, 0.33273944], + [0.73811269, 0.28137168, 0.67521429]]]) + + >>> # Ellipsis batch matrix multiplication + >>> print(paddle.einsum('...jk, ...kl->...jl', A,B)) + Tensor(shape=[2, 3, 3], dtype=float32, place=Place(cpu), stop_gradient=True, + [[[0.36321065, 0.42009076, 0.40849245], + [0.74353045, 0.79189068, 0.81345987], + [0.90488225, 0.79786193, 0.93451476]], + [[0.12680580, 1.06945944, 0.79821426], + [0.07774551, 0.55068684, 0.44512171], + [0.08053084, 0.80583858, 0.56031936]]]) """ import os