!1354 update include file 0325

From: @shenwei41
Reviewed-by: @lilongfei15,@xsmq
Signed-off-by: @xsmq
pull/1354/MERGE
mindspore-ci-bot 4 years ago committed by Gitee
commit 168508b063

@ -1444,8 +1444,7 @@ REG_OP(MaxPoolV3Grad)
*@par Inputs: *@par Inputs:
*x: A tensor of shape is 4d, format is support NHWC. *x: A tensor of shape is 4d, format is support NHWC.
*filter: A tensor of shape is 3d, the type is same with x, *filter: A tensor of shape is 3d, the type is same with x, and the c dimension is same with x. \n
and the c dimension is same with x. \n
*@par Attributes: *@par Attributes:
*@li strides: A required list of 4 ints, specifying the stride of the sliding window. The strides of the N and C dimensions are 1. *@li strides: A required list of 4 ints, specifying the stride of the sliding window. The strides of the N and C dimensions are 1.
@ -1473,6 +1472,82 @@ REG_OP(Dilation2D)
.ATTR(data_format, String, "NHWC") .ATTR(data_format, String, "NHWC")
.OP_END_FACTORY_REG(Dilation2D) .OP_END_FACTORY_REG(Dilation2D)
/*
* @brief Performs Dilation2DBackpropFilter on the input. \n
*@par Inputs:
*x: A tensor of shape is 4d, format is support NHWC
*filter: A tensor of shape is 3d the type is same with x,
*out_backprop: Has the same type and format as input "x" and the c dimension is same with x. \n
*@par Attributes
*@li stride: A required list of 4 ints, specifying the stride of the sliding window. The strides of the N and C
dimension are 1
*@li rates: A required list of 4 ints, the rates of the N and C dimensions are 1
*@li padding_mode: A optional string. Defaults to "SAME", it support SAME and VALID
*@li pads: A optional list of 4 ints. \n
*@par Outputs:
*y: The output tensor. Has the same type and format as input "filter" . \n
*@par Third-party framework compatibility
* Compatible with the TensorFlow operator Dilation2D
*/
REG_OP(Dilation2DBackpropFilter)
.INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64, DT_UINT8, DT_INT16, DT_INT8, DT_UINT16}))
.INPUT(filter,
TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64, DT_UINT8, DT_INT16, DT_INT8, DT_UINT16}))
.INPUT(out_backprop,
TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64, DT_UINT8, DT_INT16, DT_INT8, DT_UINT16}))
.OUTPUT(y,
TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64, DT_UINT8, DT_INT16, DT_INT8, DT_UINT16}))
.REQUIRED_ATTR(strides, ListInt)
.REQUIRED_ATTR(rates, ListInt)
.ATTR(padding_mode, String, "SAME")
.ATTR(pads, ListInt, {0, 0, 0, 0})
.ATTR(ceil_mode, Bool, false)
.ATTR(data_format, String, "NHWC")
.OP_END_FACTORY_REG(Dilation2DBackpropFilter)
/*
* @brief Performs Dilation2DBackpropInput on the input. \n
*@par Inputs:
*x: A tensor of shape is 4d, format is support NHWC
*filter: A tensor of shape is 3d the type is same with x,
*out_backprop: Has the same type and format as input "x" and the c dimension is same with x. \n
*@par Attributes
*@li stride: A required list of 4 ints, specifying the stride of the sliding window. The strides of the N and C
dimension are 1
*@li rates: A required list of 4 ints, the rates of the N and C dimensions are 1
*@li padding_mode: A optional string. Defaults to "SAME", it support SAME and VALID
*@li pads: A optional list of 4 ints. \n
*@par Outputs:
*y: The output tensor. Has the same type and format as input "filter" . \n
*@par Third-party framework compatibility
* Compatible with the TensorFlow operator Dilation2D
*/
REG_OP(Dilation2DBackpropInput)
.INPUT(x, TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64, DT_UINT8, DT_INT16, DT_INT8, DT_UINT16}))
.INPUT(filter,
TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64, DT_UINT8, DT_INT16, DT_INT8, DT_UINT16}))
.INPUT(out_backprop,
TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64, DT_UINT8, DT_INT16, DT_INT8, DT_UINT16}))
.OUTPUT(y,
TensorType({DT_FLOAT16, DT_FLOAT, DT_DOUBLE, DT_INT32, DT_INT64, DT_UINT8, DT_INT16, DT_INT8, DT_UINT16}))
.REQUIRED_ATTR(strides, ListInt)
.REQUIRED_ATTR(rates, ListInt)
.ATTR(padding_mode, String, "SAME")
.ATTR(pads, ListInt, {0, 0, 0, 0})
.ATTR(ceil_mode, Bool, false)
.ATTR(data_format, String, "NHWC")
.OP_END_FACTORY_REG(Dilation2DBackpropInput)
/** /**
* @brief Applies a 2D adaptive average pooling over * @brief Applies a 2D adaptive average pooling over
* an input signal composed of several input planes. \n * an input signal composed of several input planes. \n

@ -74,6 +74,7 @@ enum MsprofReporterCallbackType {
MSPROF_REPORTER_REPORT = 0, // report data MSPROF_REPORTER_REPORT = 0, // report data
MSPROF_REPORTER_INIT, // init reporter MSPROF_REPORTER_INIT, // init reporter
MSPROF_REPORTER_UNINIT, // uninit reporter MSPROF_REPORTER_UNINIT, // uninit reporter
MSPROF_REPORTER_DATA_MAX_LEN, // data max length for calling report callback
}; };
/** /**

@ -41,10 +41,10 @@ namespace Engine {
* the Reporter class .used to send data to profiling * the Reporter class .used to send data to profiling
*/ */
class MSVP_PROF_API Reporter { class MSVP_PROF_API Reporter {
public: public:
virtual ~Reporter() {} virtual ~Reporter() {}
public: public:
/** /**
* @ingroup reporter * @ingroup reporter
* @name : Report * @name : Report
@ -77,6 +77,8 @@ class MSVP_PROF_API Reporter {
* @see ProfMgrStop * @see ProfMgrStop
*/ */
virtual int Flush() = 0; virtual int Flush() = 0;
virtual uint32_t GetReportDataMaxLen() = 0;
}; };
} // namespace Engine } // namespace Engine

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