【PIR API adaptor No.35、40】 Migrate paddle.nn.ChannelShuffle/ClipGradByNorm into pir #59718
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… my-cool-stuff
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你的PR提交成功，感谢你对开源项目的贡献! |
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需要pre-commit 处理下代码风格的问题 |
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也要打开 check_pir 开关
self.check_output_with_place(place, atol=0.001, check_pir=True)|
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| def test_check_grad(self): | ||
| self.check_grad(['X'], 'Out') | ||
| self.check_grad(['X'], 'Out',check_pir=True) | ||
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| class TestChannelLast(TestChannelShuffleOp): |
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该单侧下的 test_static_graph_functional，test_static_graph_layer 需要用 test_with_pir_api 修饰。run_dygraph 不需要，因为其为动态图单测
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test_static_graph_functional，test_static_graph_layer 打开后报错
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test_static_graph_functional 和 test_static_graph_layer 的单测中所有的：
base.default_main_program() 替换为 paddle.static.default_main_program() 即可解决错误
| @@ -162,7 +162,7 @@ def test_static_graph_layer(self): | |||
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| np.testing.assert_allclose(res_1[0], out_1_np) | |||
| np.testing.assert_allclose(res_2[0], out_2_np) | |||
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| @test_with_pir_api | |||
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| @test_with_pir_api |
| @@ -200,10 +200,10 @@ def run_dygraph(self, groups, data_format): | |||
| if data_format != 'NCHW': | |||
| channel_shuffle_str += f', data_format={data_format}' | |||
| self.assertEqual(channel_shuffle.extra_repr(), channel_shuffle_str) | |||
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| @test_with_pir_api | |||
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| @test_with_pir_api |
| def test_dygraph1(self): | ||
| self.run_dygraph(3, "NCHW") | ||
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| @test_with_pir_api |
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| @test_with_pir_api |
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该文件下的 TestChannelShuffleError 是否支持 pir 模式？若不支持麻烦在 pr 描述里说明，方便我们后续 fix
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Description
PIR API 推全升级
paddle.nn.ClipGradByNorm引用了clip_by_norm，对clip_by_norm迁移升级至 pir，并更新单测，test_clip_by_norm_op单测覆盖率：4/4 test_gradient_clip 单测覆盖率：0/2paddle.nn.ChannelShuffle引用了paddle.nn.functional.channel_shuffle，对channel_shuffle迁移升级至 pir，并更新单测， 单测覆盖率：6/6（TestChannelShuffleError 通过）test_gradient_clip报错：
