【UnitTestFix No.6】test_gather_op 单测 优化及新增特性

[aztice]

PR Category

Operator Mechanism

PR Types

New features

Description

由于PR Types只给选择一个类型，其实我建议可以改成两个，具体直接在下面标注了
增强特性

将所有 paddle.disable_static() 以及 paddle.enable_static() 以 with paddle.base.dygraph.guard() 代替，同时建议在后续可能存在的新feature采用自动的 disable + enable，避免意外。

新增特性

新增了 GPU + CPU 的一致性检查。

@unittest.skipIf(
    not (core.is_compiled_with_cuda() or is_custom_device()),
    "only support compiled with CUDA.",
)
class TestGatherGPUCPUConsistency(unittest.TestCase):
    def test_gpu_cpu_consistency(self):
        with paddle.base.dygraph.guard():
            np.random.seed(42)
            x = np.random.rand(1000, 128).astype("float32")
            index = np.random.randint(0, 1000, size=(100,))
            cpu_out = paddle.gather(
                paddle.to_tensor(x, place=paddle.CPUPlace()),
                paddle.to_tensor(index),
            )
            gpu_out = paddle.gather(
                paddle.to_tensor(x, place=paddle.CUDAPlace(0)),
                paddle.to_tensor(index),
            )
            np.testing.assert_allclose(
                cpu_out.numpy(), gpu_out.numpy(), rtol=1e-6
            )

Result

/opt/conda/envs/python35-paddle120-env/lib/python3.10/site-packages/paddle/base/framework.py:722: VisibleDeprecationWarning: 
Warning:
API "paddle.base.dygraph.tensor_patch_methods.gradient" is deprecated since 2.1.0, and will be removed in future versions.
    Reason: Please use tensor.grad, which returns the tensor value of the gradient. 
  return func(*args, **kwargs)
...........
----------------------------------------------------------------------
Ran 129 tests in 84.951s

OK

As a result, OK nya~

@luotao1 @YqGe585

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[YqGe585]

LGTM

[aztice]

/re-run all-failed

[aztice]

/re-run all-failed

[aztice]

Notice

本单测的guard疑似出现问题，已还原。

[aztice]

Windows CI似乎有问题，这边看到一个没有Response，一个一秒就失败了，check approval可以忽略通常。

[aztice]

/re-run all-failed

[YqGe585]

LGTM

[aztice]

/re-run all-failed

[aztice]

/re-run all-failed