池化类算子proto新增宏隔离-ops-nn-AtomGit

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已合并

池化类算子proto新增宏隔离 #8435

小王！创建于 24 天前从qq_52056150/ops-nn： fix/add-pooling-proto-macro-guards 合入到 cann/ops-nn： master

池化类算子proto新增宏隔离 #8435

已合并

小王！创建于 24 天前

从qq_52056150/ops-nn fix/add-pooling-proto-macro-guards合入到cann/ops-nn master

共 9 个文件变更+32-5

Mpooling/adaptive_avg_pool2d/op_graph/adaptive_avg_pool2d_proto.h+4-1

	@@ -39,11 +39,14 @@ namespace ge {
39	* @par Third-party framework compatibility	39	* @par Third-party framework compatibility
40	* Compatible with the Pytorch operator AdaptiveAvgPool2d.	40	* Compatible with the Pytorch operator AdaptiveAvgPool2d.
41	*/	41	*/
		42	+#ifndef OPS_PROTO_DEF_ADAPTIVEAVGPOOL2D
		43	+#define OPS_PROTO_DEF_ADAPTIVEAVGPOOL2D
42	REG_OP(AdaptiveAvgPool2d)	44	REG_OP(AdaptiveAvgPool2d)
43	.INPUT(x, TensorType({DT_FLOAT, DT_FLOAT16, DT_BF16}))	45	.INPUT(x, TensorType({DT_FLOAT, DT_FLOAT16, DT_BF16}))
44	.OUTPUT(y, TensorType({DT_FLOAT, DT_FLOAT16, DT_BF16}))	46	.OUTPUT(y, TensorType({DT_FLOAT, DT_FLOAT16, DT_BF16}))
45	.REQUIRED_ATTR(output_size, ListInt)	47	.REQUIRED_ATTR(output_size, ListInt)
46	.OP_END_FACTORY_REG(AdaptiveAvgPool2d)	48	.OP_END_FACTORY_REG(AdaptiveAvgPool2d)
		49	+#endif
47	} // namespace ge	50	} // namespace ge
48		51
49	-#endif // OPS_POOLING_ADAPTIVE_AVG_POOL2D_PROTO_H_	52	+#endif // OPS_POOLING_ADAPTIVE_AVG_POOL2D_PROTO_H_

Mpooling/adaptive_avg_pool2d_grad/op_graph/adaptive_avg_pool2d_grad_proto.h+3-0

	@@ -35,11 +35,14 @@ namespace ge {
35	* @par Third-party framework compatibility	35	* @par Third-party framework compatibility
36	* Compatible with the Pytorch operator AdaptiveAvgPool2dGrad.	36	* Compatible with the Pytorch operator AdaptiveAvgPool2dGrad.
37	*/	37	*/
		38	+#ifndef OPS_PROTO_DEF_ADAPTIVEAVGPOOL2DGRAD
		39	+#define OPS_PROTO_DEF_ADAPTIVEAVGPOOL2DGRAD
38	REG_OP(AdaptiveAvgPool2dGrad)	40	REG_OP(AdaptiveAvgPool2dGrad)
39	.INPUT(input_grad, TensorType({DT_FLOAT, DT_FLOAT16, DT_BF16}))	41	.INPUT(input_grad, TensorType({DT_FLOAT, DT_FLOAT16, DT_BF16}))
40	.OUTPUT(output_grad, TensorType({DT_FLOAT, DT_FLOAT16, DT_BF16}))	42	.OUTPUT(output_grad, TensorType({DT_FLOAT, DT_FLOAT16, DT_BF16}))
41	.REQUIRED_ATTR(orig_input_shape, ListInt)	43	.REQUIRED_ATTR(orig_input_shape, ListInt)
42	.OP_END_FACTORY_REG(AdaptiveAvgPool2dGrad)	44	.OP_END_FACTORY_REG(AdaptiveAvgPool2dGrad)
		45	+#endif
43		46
44	} // namespace ge	47	} // namespace ge
45	#endif // OPS_POOLING_ADAPTIVE_AVG_POOL2D_GRAD_PROTO_H_	48	#endif // OPS_POOLING_ADAPTIVE_AVG_POOL2D_GRAD_PROTO_H_

Mpooling/avg_pool_grad/op_graph/avg_pool_grad_proto.h+3-0

	@@ -51,6 +51,8 @@ namespace ge {
51	* @par Third-party framework compatibility	51	* @par Third-party framework compatibility
52	* @li Compatible with the TensorFlow operator AvgPoolGrad.	52	* @li Compatible with the TensorFlow operator AvgPoolGrad.
53	*/	53	*/
		54	+#ifndef OPS_PROTO_DEF_AVGPOOLGRAD
		55	+#define OPS_PROTO_DEF_AVGPOOLGRAD
54	REG_OP(AvgPoolGrad)	56	REG_OP(AvgPoolGrad)
55	.INPUT(orig_input_shape, TensorType({DT_INT32}))	57	.INPUT(orig_input_shape, TensorType({DT_INT32}))
56	.INPUT(input_grad, TensorType({DT_FLOAT16, DT_FLOAT32, DT_DOUBLE, DT_BF16}))	58	.INPUT(input_grad, TensorType({DT_FLOAT16, DT_FLOAT32, DT_DOUBLE, DT_BF16}))
	@@ -60,6 +62,7 @@ REG_OP(AvgPoolGrad)
60	.REQUIRED_ATTR(padding, String)	62	.REQUIRED_ATTR(padding, String)
61	.ATTR(data_format, String, "NHWC")	63	.ATTR(data_format, String, "NHWC")
62	.OP_END_FACTORY_REG(AvgPoolGrad)	64	.OP_END_FACTORY_REG(AvgPoolGrad)
		65	+#endif
63		66
64	} // namespace ge	67	} // namespace ge
65	#endif // OP_PROTO_AVG_POOL_GRAD_H_	68	#endif // OP_PROTO_AVG_POOL_GRAD_H_

Mpooling/avg_pool_v2_grad/op_graph/avg_pool_v2_grad_proto.h+4-1

	@@ -60,6 +60,8 @@ namespace ge {
60	* @par Third-party framework compatibility	60	* @par Third-party framework compatibility
61	* @li Compatible with the TensorFlow operator AvgPoolGrad.	61	* @li Compatible with the TensorFlow operator AvgPoolGrad.
62	*/	62	*/
		63	+#ifndef OPS_PROTO_DEF_AVGPOOLV2GRAD
		64	+#define OPS_PROTO_DEF_AVGPOOLV2GRAD
63	REG_OP(AvgPoolV2Grad)	65	REG_OP(AvgPoolV2Grad)
64	.INPUT(orig_input_shape, TensorType({DT_INT32}))	66	.INPUT(orig_input_shape, TensorType({DT_INT32}))
65	.INPUT(input_grad, TensorType({DT_FLOAT16, DT_FLOAT32, DT_DOUBLE, DT_BF16}))	67	.INPUT(input_grad, TensorType({DT_FLOAT16, DT_FLOAT32, DT_DOUBLE, DT_BF16}))
	@@ -74,6 +76,7 @@ REG_OP(AvgPoolV2Grad)
74	.ATTR(exclusive, Bool, true)	76	.ATTR(exclusive, Bool, true)
75	.ATTR(divisor_override, Int, 0)	77	.ATTR(divisor_override, Int, 0)
76	.OP_END_FACTORY_REG(AvgPoolV2Grad)	78	.OP_END_FACTORY_REG(AvgPoolV2Grad)
		79	+#endif
77		80
78	} // namespace ge	81	} // namespace ge
79	-#endif // OP_PROTO_AVG_POOL_V2_GRAD_H_	82	+#endif // OP_PROTO_AVG_POOL_V2_GRAD_H_

Mpooling/max_pool3d_grad/op_graph/max_pool3d_grad_proto.h+3-0

	@@ -59,6 +59,8 @@ and VALID.
59	* @par Third-party framework compatibility	59	* @par Third-party framework compatibility
60	* Compatible with the Torch operator MaxPool3DGrad.	60	* Compatible with the Torch operator MaxPool3DGrad.
61	*/	61	*/
		62	+#ifndef OPS_PROTO_DEF_MAXPOOL3DGRAD
		63	+#define OPS_PROTO_DEF_MAXPOOL3DGRAD
62	REG_OP(MaxPool3DGrad)	64	REG_OP(MaxPool3DGrad)
63	.INPUT(orig_x, TensorType::RealNumberType())	65	.INPUT(orig_x, TensorType::RealNumberType())
64	.INPUT(orig_y, TensorType::RealNumberType())	66	.INPUT(orig_y, TensorType::RealNumberType())
	@@ -70,5 +72,6 @@ REG_OP(MaxPool3DGrad)
70	.REQUIRED_ATTR(pads, ListInt)	72	.REQUIRED_ATTR(pads, ListInt)
71	.ATTR(data_format, String, "NDHWC")	73	.ATTR(data_format, String, "NDHWC")
72	.OP_END_FACTORY_REG(MaxPool3DGrad)	74	.OP_END_FACTORY_REG(MaxPool3DGrad)
		75	+#endif
73	} // namespace ge	76	} // namespace ge
74	#endif // OPS_BUILT_IN_OP_PROTO_INC_MAX_POOL3D_GRAD_PROTO_H_	77	#endif // OPS_BUILT_IN_OP_PROTO_INC_MAX_POOL3D_GRAD_PROTO_H_

Mpooling/max_pool3d_grad_with_argmax/op_graph/max_pool_grad_with_argmax_v1_proto.h+4-1

	@@ -61,6 +61,8 @@ mask.
61	* Compatible with the PyTorch backward operator of max_pool2d_with_indices.	61	* Compatible with the PyTorch backward operator of max_pool2d_with_indices.
62	*/	62	*/
63		63
		64	+#ifndef OPS_PROTO_DEF_MAXPOOLGRADWITHARGMAXV1
		65	+#define OPS_PROTO_DEF_MAXPOOLGRADWITHARGMAXV1
64	REG_OP(MaxPoolGradWithArgmaxV1)	66	REG_OP(MaxPoolGradWithArgmaxV1)
65	.INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT}))	67	.INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT}))
66	.INPUT(grad, TensorType({DT_FLOAT16, DT_FLOAT}))	68	.INPUT(grad, TensorType({DT_FLOAT16, DT_FLOAT}))
	@@ -73,5 +75,6 @@ REG_OP(MaxPoolGradWithArgmaxV1)
73	.ATTR(dilation, ListInt, {1, 1, 1, 1})	75	.ATTR(dilation, ListInt, {1, 1, 1, 1})
74	.ATTR(ceil_mode, Bool, false)	76	.ATTR(ceil_mode, Bool, false)
75	.OP_END_FACTORY_REG(MaxPoolGradWithArgmaxV1)	77	.OP_END_FACTORY_REG(MaxPoolGradWithArgmaxV1)
		78	+#endif
76	} // namespace ge	79	} // namespace ge
77	-#endif	80	+#endif

Mpooling/max_pool3d_with_argmax_v2/op_graph/max_pool_with_argmax_v1_proto.h+4-1

	@@ -54,6 +54,8 @@ mask. \n
54	* @par Third-party framework compatibility	54	* @par Third-party framework compatibility
55	* Compatible with the PyTorch operator max_pool2d_with_indices.	55	* Compatible with the PyTorch operator max_pool2d_with_indices.
56	*/	56	*/
		57	+#ifndef OPS_PROTO_DEF_MAXPOOLWITHARGMAXV1
		58	+#define OPS_PROTO_DEF_MAXPOOLWITHARGMAXV1
57	REG_OP(MaxPoolWithArgmaxV1)	59	REG_OP(MaxPoolWithArgmaxV1)
58	.INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT32}))	60	.INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT32}))
59	.OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT32}))	61	.OUTPUT(y, TensorType({DT_FLOAT16, DT_FLOAT32}))
	@@ -65,6 +67,7 @@ REG_OP(MaxPoolWithArgmaxV1)
65	.ATTR(dilation, ListInt, {1, 1, 1, 1})	67	.ATTR(dilation, ListInt, {1, 1, 1, 1})
66	.ATTR(ceil_mode, Bool, false)	68	.ATTR(ceil_mode, Bool, false)
67	.OP_END_FACTORY_REG(MaxPoolWithArgmaxV1)	69	.OP_END_FACTORY_REG(MaxPoolWithArgmaxV1)
		70	+#endif
68		71
69	} // namespace ge	72	} // namespace ge
70	-#endif	73	+#endif

Mpooling/max_pool_grad/op_graph/max_pool_grad_proto.h+3-0

	@@ -45,6 +45,8 @@ namespace ge {
45	* @par Third-party framework compatibility	45	* @par Third-party framework compatibility
46	* Compatible with the TensorFlow operator MaxPoolGrad.	46	* Compatible with the TensorFlow operator MaxPoolGrad.
47	*/	47	*/
		48	+#ifndef OPS_PROTO_DEF_MAXPOOLGRAD
		49	+#define OPS_PROTO_DEF_MAXPOOLGRAD
48	REG_OP(MaxPoolGrad)	50	REG_OP(MaxPoolGrad)
49	.INPUT(x1, TensorType::RealNumberType())	51	.INPUT(x1, TensorType::RealNumberType())
50	.INPUT(x2, TensorType::RealNumberType())	52	.INPUT(x2, TensorType::RealNumberType())
	@@ -55,6 +57,7 @@ REG_OP(MaxPoolGrad)
55	.REQUIRED_ATTR(padding, String)	57	.REQUIRED_ATTR(padding, String)
56	.ATTR(data_format, String, "NHWC")	58	.ATTR(data_format, String, "NHWC")
57	.OP_END_FACTORY_REG(MaxPoolGrad)	59	.OP_END_FACTORY_REG(MaxPoolGrad)
		60	+#endif
58	} // namespace ge	61	} // namespace ge
59		62
60	#endif // OPS_BUILT_IN_OP_PROTO_INC_NN_POOLING_OPS_H	63	#endif // OPS_BUILT_IN_OP_PROTO_INC_NN_POOLING_OPS_H

Mpooling/max_pool_v3/op_graph/max_pool_proto.h+4-1

	@@ -61,6 +61,8 @@ namespace ge {
61	* @par Third-party framework compatibility	61	* @par Third-party framework compatibility
62	* Compatible with the TensorFlow operator MaxPool.	62	* Compatible with the TensorFlow operator MaxPool.
63	*/	63	*/
		64	+#ifndef OPS_PROTO_DEF_MAXPOOL
		65	+#define OPS_PROTO_DEF_MAXPOOL
64	REG_OP(MaxPool)	66	REG_OP(MaxPool)
65	.INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT32, DT_DOUBLE, DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16,	67	.INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT32, DT_DOUBLE, DT_INT8, DT_INT16, DT_INT32, DT_INT64, DT_UINT8, DT_UINT16,
66	DT_QINT8}))	68	DT_QINT8}))
	@@ -71,6 +73,7 @@ REG_OP(MaxPool)
71	.REQUIRED_ATTR(padding, String)	73	.REQUIRED_ATTR(padding, String)
72	.ATTR(data_format, String, "NHWC")	74	.ATTR(data_format, String, "NHWC")
73	.OP_END_FACTORY_REG(MaxPool)	75	.OP_END_FACTORY_REG(MaxPool)
		76	+#endif
74		77
75	} // namespace ge	78	} // namespace ge
76	-#endif	79	+#endif