forked from mindspore-Ecosystem/mindspore
load super bar by json
This commit is contained in:
jiaorui
parent
bcf95a70c4
commit
fa1b5a1b7f
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@ -386,6 +386,7 @@ install(
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## config files
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install(
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FILES ${CMAKE_SOURCE_DIR}/config/op_info.config
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FILES ${CMAKE_SOURCE_DIR}/config/super_bar_config.json
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DESTINATION ${INSTALL_CFG_DIR}
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COMPONENT mindspore
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)
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@ -180,6 +180,7 @@ install(
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## config files
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install(
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FILES ${CMAKE_SOURCE_DIR}/config/op_info.config
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FILES ${CMAKE_SOURCE_DIR}/config/super_bar_config.json
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DESTINATION ${INSTALL_CFG_DIR}
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COMPONENT mindspore
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)
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@ -0,0 +1,439 @@
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{
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"NodeAttrMap": {
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"AvgPool3DD": {
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"ksize": "kernel_size",
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"pads": "pad_list",
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"data_format": "format"
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},
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"AvgPool3DGradD": {
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"orig_input_shape": "origin_input_shape",
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"ksize": "kernel_size",
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"pads": "pad_list",
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"data_format": "format"
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},
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"AvgPoolGradD": {
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"orig_input_shape": "x_origin",
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"ksize": "kernel_size",
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"padding": "pad_mode",
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"data_format": "format"
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},
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"AccumulateNV2": {
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"N": "n"
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},
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"AddN": {
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"N": "n"
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},
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"Conv2D": {
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"strides": "stride",
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"pads": "pad_list",
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"dilations": "dilation",
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"data_format": "format"
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},
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"Conv3DTransposeD": {
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"pads": "pad_list",
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"data_format": "format"
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},
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"Conv3D": {
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"pads": "pad_list",
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"data_format": "format"
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},
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"Conv3DBackpropInputD": {
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"pads": "pad_list",
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"data_format": "format"
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},
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"Conv3DBackpropFilterD": {
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"pads": "pad_list",
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"data_format": "format"
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},
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"Conv2DTransposeD": {
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"input_size": "input_sizes",
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"strides": "stride",
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"pads": "pad_list",
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"dilations": "dilation",
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"data_format": "format"
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},
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"MaxPoolWithArgmax": {
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"ksize": "kernel_size",
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"padding": "pad_mode"
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},
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"SoftmaxGradExt": {
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"axes": "axis",
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"keep_dims": "keepdims"
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},
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"Conv2DBackpropFilterD": {
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"filter_size": "filter_sizes",
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"strides": "stride",
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"pads": "pad_list",
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"dilations": "dilation",
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"data_format": "format"
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},
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"Conv2DBackpropInputD": {
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"input_size": "input_sizes",
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"strides": "stride",
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"pads": "pad_list",
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"dilations": "dilation",
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"data_format": "format"
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},
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"Conv2DBackpropFilter": {
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"strides": "stride",
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"pads": "pad_list",
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"dilations": "dilation",
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"data_format": "format"
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},
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"Conv2DBackpropInput": {
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"strides": "stride",
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"pads": "pad_list",
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"dilations": "dilation",
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"data_format": "format"
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},
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"ConcatD": {
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"concat_dim": "axis"
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},
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"DepthwiseConv2D": {
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"strides": "stride",
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"dilations": "dilation",
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"pads": "pad_list",
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"data_format": "format",
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"offfset_x": "offset_a"
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},
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"ExtractVolumePatches": {
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"ksizes": "kernel_size"
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},
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"L2Normalize": {
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"eps": "epsilon"
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},
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"L2NormalizeGrad": {
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"dim": "axis",
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"eps": "epsilon"
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},
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"MaxPoolGradWithArgmax": {
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"ksize": "kernel_size",
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"padding": "pad_mode"
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},
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"BiasAddGrad": {
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"data_format": "format"
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},
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"FusedDbnDw": {
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"filter_size": "filter_sizes",
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"strides": "stride",
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"pads": "pad_list",
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"dilations": "dilation",
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"data_format": "format"
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},
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"MaxPool": {
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"ksize": "kernel_size",
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"padding": "pad_mode",
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"data_format": "format"
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},
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"ReduceMeanD": {
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"axes": "axis"
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},
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"ReduceSumD": {
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"axes": "axis"
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},
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"ReduceAnyD": {
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"axes": "axis"
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},
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"ReduceMaxD": {
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"axes": "axis"
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},
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"ReduceMinD": {
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"axes": "axis"
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},
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"ReduceAllD": {
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"axes": "axis"
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},
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"ReduceProdD": {
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"axes": "axis"
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},
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"ReduceStd": {
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"dim": "axis",
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"keepdim": "keep_dims"
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},
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"SoftmaxV2": {
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"axes": "axis"
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},
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"LogSoftmaxV2": {
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"axes": "axis"
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},
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"ArgMaxD": {
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"dimension": "axis"
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},
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"BatchMatMul": {
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"adj_x1": "transpose_x1",
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"adj_x2": "transpose_x2"
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},
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"BatchMatMulV2": {
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"adj_x1": "transpose_x1",
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"adj_x2": "transpose_x2"
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},
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"BatchNormal": {
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"data_format": "format"
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},
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"ArgMaxWithValue": {
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"dimension": "axis"
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},
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"SplitD": {
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"split_dim": "axis",
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"num_split": "output_num"
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},
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"BiasAdd": {
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"data_format": "format"
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},
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"SliceD": {
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"offsets": "begin"
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},
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"MaxPoolGrad": {
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"ksize": "kernel_size",
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"padding": "pad_mode",
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"data_format": "format"
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},
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"MaxPool3D": {
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"ksize": "kernel_size",
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"padding": "pad_mode",
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"pads": "pad_list",
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"data_format": "format"
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},
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"MaxPool3DGrad": {
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"ksize": "kernel_size",
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"padding": "pad_mode",
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"pads": "pad_list",
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"data_format": "format"
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},
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"MaxPoolGradGrad": {
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"ksize": "kernel_size",
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"padding": "pad_mode",
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"data_format": "format"
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},
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"AvgPool": {
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"ksize": "kernel_size",
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"padding": "pad_mode",
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"data_format": "format"
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},
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"BatchNorm": {
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"data_format": "format"
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},
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"BatchNormGrad": {
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"data_format": "format"
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},
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"ArgMin": {
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"dimension": "axis"
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},
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"ArgMinD": {
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"dimension": "axis"
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},
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"LpNorm": {
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"axes": "axis",
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"keepdim": "keep_dims"
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},
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"SmoothL1LossV2": {
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"sigma": "beta"
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},
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"Roll": {
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"shifts": "shift",
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"dims": "axis"
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},
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"SmoothL1LossGradV2": {
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"sigma": "beta"
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},
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"Centralization": {
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"axes": "axis"
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},
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"MaxPool3DGradGradD": {
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"ksize": "kernel_size"
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}
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},
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"AttrDefaultValue": {
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"Log": {
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"base": "-1.0",
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"scale": "1.0",
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"shift": "0.0"
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},
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"ScatterNdUpdate": {
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"use_locking": "false"
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},
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"OneHotD": {
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"axis": "-1"
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},
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"Iou": {
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"mode": "iou",
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"eps": "1.0"
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},
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"GatherV2D": {
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"axis": "-1"
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},
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"MaxPoolGrad": {
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"data_format": "NHWC"
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},
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"ResizeNearestNeighborV2D": {
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"align_corners": "false",
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"half_pixel_centers": "false"
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},
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"ResizeNearestNeighborV2GradD": {
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"align_corners": "false",
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"half_pixel_centers": "false"
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},
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"MaxPool3D": {
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"pads": "0,0,0",
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"dilation": "1,1,1",
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"ceil_mode": "0"
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}
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},
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"InputOrders": {
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"LogSoftmaxGrad": [
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1,
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0
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],
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"LayerNormGrad": [
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1,
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0,
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2,
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3,
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4
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],
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"LayerNormBetaGammaBackprop": [
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1,
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0,
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2,
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3
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],
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"LayerNormXBackprop": [
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1,
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0,
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2,
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3,
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4
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],
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"LayerNormXBackpropV2": [
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1,
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0,
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2,
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3,
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4
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],
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"ApplyCenteredRMSPropD": [
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0,
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1,
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2,
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3,
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5,
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6,
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7,
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8,
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4
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],
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"Conv2DBackpropInputD": [
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1,
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0
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],
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"Conv2DBackpropFilterD": [
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1,
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0
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],
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"MinimumGrad": [
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2,
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0,
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1
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],
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"MaximumGrad": [
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2,
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0,
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1
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],
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"StridedSliceGrad": [
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1,
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2,
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3,
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4,
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0
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],
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"Conv2DBackpropInput": [
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2,
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1,
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0
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],
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"Conv2DBackpropFilter": [
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1,
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2,
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0
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],
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"FusionOp_Conv2DBackpropInputD_AddN_ReluGradV2": [
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1,
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0,
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2,
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3
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],
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"FusionOp_Conv2DBackpropInputD_ReluGradV2": [
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1,
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0,
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2
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]
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},
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"SkipDynamicCompileStatic": [
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"SoftmaxV2",
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"PRelu",
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"Trunc",
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"AccumulateNV2",
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"SoftmaxCrossEntropyWithLogits",
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"ReduceMeanD",
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"SquareSumV1",
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"BiasAddGrad"
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],
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"SkipNodesComments": {
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"BroadcastTo": "The name is occupied",
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"DynamicBroadcastTo ": "The name is occupied",
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"BatchToSpaceD ": "attr type is listInt，not listListInt",
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"BatchToSpaceNDD ": "attr type is listInt，not listListInt",
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"SpaceToBatchD ": "attr type is listInt，not listListInt",
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"SpaceToBatchNDD ": "attr type is listInt，not listListInt",
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"DynamicGRUV2": "input4 is None, GE will change to hidden op by pass",
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"DynamicRNN ": "input4 is None, GE will change to hidden op by pass",
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"KLDivLossGrad": " Accuracy issues",
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"ScatterNdUpdate": " not support int8 in op json",
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"ScatterNdAdd": "not support int8 in op json",
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"UnsortedSegmentSum ": " check support failed when shape is -2",
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"ConcatOffset": "Hadn't adapted tbe implementation",
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"MirrorPad ": "Hadn't adapted tbe implementation",
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"InplaceIndexAdd": "check support failed if var has only one dimension",
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"Expand": "Hadn't adapted tbe implementation",
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"ExpandD": "Hadn't adapted tbe implementation",
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"Cross ": "Hadn't adapted tbe implementation",
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"LinSpaceD": "Hadn't adapted tbe implementation",
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"Cast ": "Accuracy issues",
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"AvgPool3DGradD": "second device format is facz_3d, but in json, the key is ndhwc",
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"DataFormatDimMap ": "attr order swap",
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"DepthwiseConv2D": "Accuracy issues(second format is error in python)",
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"ACos": "dynamic impl error",
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"TransData ": "support boll",
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"ScatterNdD ": "Accuracy issues",
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"Trace": "Hadn't adapted tbe implementation"
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},
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"SkipNodes": [
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"BroadcastTo",
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"DynamicBroadcastTo",
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"BatchToSpaceD",
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"BatchToSpaceNDD",
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"SpaceToBatchD",
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"SpaceToBatchNDD",
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"DynamicGRUV2",
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"DynamicRNN",
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"KLDivLossGrad",
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"ScatterNdUpdate",
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"ScatterNdAdd",
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"ConcatOffset",
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"MirrorPad",
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"InplaceIndexAdd",
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"Expand",
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"ExpandD",
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"Cross",
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"LinSpaceD",
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"Cast",
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"AvgPool3DGradD",
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"DataFormatDimMap",
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"DepthwiseConv2D",
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"Trace",
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"ACos",
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"TransData",
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"ScatterNdD"
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]
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}
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@ -27,8 +27,10 @@
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#include "kernel/oplib/super_bar.h"
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#include "kernel/oplib/oplib.h"
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#include "utils/file_utils.h"
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#include "utils/dlopen_macro.h"
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namespace mindspore::kernel {
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namespace {
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constexpr auto kVersion910A = "Ascend910A";
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constexpr auto kVersion910ProA = "Ascend910ProA";
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constexpr auto kVersion910PremiumA = "Ascend910PremiumA";
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@ -61,6 +63,55 @@ static const std::map<std::string, OpPattern> kPatternMap = {
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MS_LOG(EXCEPTION) << "Make share ptr failed: " << e.what(); \
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}
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#if !defined(_WIN32) && !defined(_WIN64)
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bool LoadSuperBarFile(nlohmann::json *super_bar) {
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Dl_info dl_info;
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if (dladdr(reinterpret_cast<void *>(LoadSuperBarFile), &dl_info) == 0) {
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MS_LOG(ERROR) << "Get dladdr error";
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return false;
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}
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std::string cur_so_path = dl_info.dli_fname;
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auto pos = cur_so_path.find_last_of(PATH_SEPARATOR);
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if (cur_so_path.empty() || pos == std::string::npos) {
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MS_LOG(ERROR) << "Current so path is empty or the path [" << cur_so_path << "] is invalid.";
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return false;
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}
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auto super_bar_path = cur_so_path.substr(0, pos) + "/../config/super_bar_config.json";
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if (super_bar_path.size() >= PATH_MAX) {
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MS_LOG(ERROR) << "Current path [" << super_bar_path << "] length " << super_bar_path.size() << " exceeds the limit "
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<< PATH_MAX;
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return false;
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}
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char real_path_mem[PATH_MAX] = {0};
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if (realpath(common::SafeCStr(super_bar_path), real_path_mem) == nullptr) {
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super_bar_path = cur_so_path.substr(0, pos) + "/../../../../config/super_bar_config.json";
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if (super_bar_path.size() >= PATH_MAX) {
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MS_LOG(ERROR) << "Current path [" << super_bar_path << "] length " << super_bar_path.size()
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<< " exceeds the limit " << PATH_MAX;
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return false;
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}
|
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if (realpath(common::SafeCStr(super_bar_path), real_path_mem) == nullptr) {
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MS_LOG(ERROR) << "The file of super_bar_config.json is not exists in path: [" << super_bar_path << "], ";
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return false;
|
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}
|
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}
|
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auto file_path = std::string(real_path_mem);
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std::ifstream file(file_path);
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if (!file.is_open()) {
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MS_LOG(ERROR) << "Open op info file failed, real_path: " << file_path;
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return false;
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||||
}
|
||||
file >> (*super_bar);
|
||||
file.close();
|
||||
return true;
|
||||
}
|
||||
#endif
|
||||
} // namespace
|
||||
|
||||
bool OpInfoUtils::GenerateOpInfos(const std::string &version) {
|
||||
// Step1: Load json file
|
||||
nlohmann::json js;
|
||||
|
|
@ -116,6 +167,14 @@ bool OpInfoUtils::GenerateOpInfos(const std::string &version) {
|
|||
}
|
||||
|
||||
bool OpInfoUtils::LoadOpInfoJson(const std::string &version, nlohmann::json *js_) {
|
||||
#if !defined(_WIN32) && !defined(_WIN64)
|
||||
nlohmann::json super_bar;
|
||||
if (!LoadSuperBarFile(&super_bar)) {
|
||||
MS_LOG(ERROR) << "Load super bar file failed.";
|
||||
return false;
|
||||
}
|
||||
SuperBar::LoadSBConfig(super_bar);
|
||||
#endif
|
||||
std::string dir = common::GetEnv("MINDSPORE_OP_INFO_JSON_PATH");
|
||||
if (dir.empty()) {
|
||||
// normal path
|
||||
|
|
|
|||
|
|
@ -97,8 +97,6 @@ bool OpLib::RegOp(const std::string &json_string, const std::string &impl_path)
|
|||
return true;
|
||||
}
|
||||
|
||||
bool OpLib::LoadSuperBarConfig(const std::string &suber_bar_config) { return SuperBar::LoadSBConfig(suber_bar_config); }
|
||||
|
||||
void OpLib::DecodeTBESpecificInfo(const nlohmann::json &obj, const std::shared_ptr<OpInfo> &op_info) {
|
||||
const std::map<std::string, kernel::OpPattern> kOpPatternMap = {
|
||||
{kFormatAgnostic, kFormatAgnosticPattern}, {kBroadcast, kBroadcastPattern}, {kReduce, kReducePattern}};
|
||||
|
|
|
|||
|
|
@ -27,8 +27,7 @@ constexpr auto kNodeName = "NodeName";
|
|||
constexpr auto kInputOrders = "InputOrders";
|
||||
constexpr auto kSkipNodes = "SkipNodes";
|
||||
constexpr auto kSkipDynamicCompileStatic = "SkipDynamicCompileStatic";
|
||||
bool SuperBar::LoadSBConfig(const std::string &super_bar_config) {
|
||||
auto js = nlohmann::json::parse(super_bar_config);
|
||||
bool SuperBar::LoadSBConfig(const nlohmann::json &js) {
|
||||
if (!LoadSBNodeAttr(js)) {
|
||||
return false;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -28,7 +28,7 @@ class BACKEND_EXPORT SuperBar {
|
|||
public:
|
||||
SuperBar() = default;
|
||||
~SuperBar() = default;
|
||||
static bool LoadSBConfig(const std::string &super_bar_config);
|
||||
static bool LoadSBConfig(const nlohmann::json &js);
|
||||
static std::string GetSBMSAttrByKernelAttr(const std::string &op_name, const std::string &attr_name);
|
||||
static std::string GetSBKernelAttrByMSAttr(const std::string &op_name, const std::string &attr_name);
|
||||
static std::string GetSBNodeAttrDefaultValue(const std::string &op_name, const std::string &attr_name);
|
||||
|
|
|
|||
|
|
@ -458,8 +458,7 @@ PYBIND11_MODULE(_c_expression, m) {
|
|||
|
||||
(void)py::class_<OpLib, std::shared_ptr<OpLib>>(m, "Oplib")
|
||||
.def(py::init())
|
||||
.def_static("reg_op", &OpLib::RegOp, "Register op info.")
|
||||
.def_static("load_super_bar_config", &OpLib::LoadSuperBarConfig, "Load super bar config.");
|
||||
.def_static("reg_op", &OpLib::RegOp, "Register op info.");
|
||||
|
||||
(void)py::class_<CollectiveManager, std::shared_ptr<CollectiveManager>>(m, "CollectiveManager")
|
||||
.def_static("get_instance", &CollectiveManager::instance, "Get collective manager instance.")
|
||||
|
|
|
|||
|
|
@ -14,7 +14,6 @@
|
|||
# ============================================================================
|
||||
|
||||
"""tbe ops"""
|
||||
from .super_bar_config import _call_super_bar_config
|
||||
from .broadcast_to import _broadcast_to_tbe # The name is occupied
|
||||
from .broadcast_to_ds import _broadcast_to_ds_tbe # The name is occupied
|
||||
from .batch_to_space import _batch_to_space_tbe # attr type is listInt，not listListInt
|
||||
|
|
|
|||
|
|
@ -1,356 +0,0 @@
|
|||
# Copyright 2020 Huawei Technologies Co., Ltd
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
# ============================================================================
|
||||
|
||||
"""Abs op"""
|
||||
from mindspore.ops.op_info_register import load_super_bar_config
|
||||
|
||||
super_bar_config = {
|
||||
"NodeAttrMap": {
|
||||
"AvgPool3DD": {
|
||||
"ksize": "kernel_size",
|
||||
"pads": "pad_list",
|
||||
"data_format": "format"
|
||||
},
|
||||
"AvgPool3DGradD": {
|
||||
"orig_input_shape": "origin_input_shape",
|
||||
"ksize": "kernel_size",
|
||||
"pads": "pad_list",
|
||||
"data_format": "format"
|
||||
},
|
||||
"AvgPoolGradD": {
|
||||
"orig_input_shape": "x_origin",
|
||||
"ksize": "kernel_size",
|
||||
"padding": "pad_mode",
|
||||
"data_format": "format"
|
||||
},
|
||||
"AccumulateNV2": {
|
||||
"N": "n"
|
||||
},
|
||||
"AddN": {
|
||||
"N": "n"
|
||||
},
|
||||
"Conv2D": {
|
||||
"strides": "stride",
|
||||
"pads": "pad_list",
|
||||
"dilations": "dilation",
|
||||
"data_format": "format"
|
||||
},
|
||||
"Conv3DTransposeD": {
|
||||
"pads": "pad_list",
|
||||
"data_format": "format"
|
||||
},
|
||||
"Conv3D": {
|
||||
"pads": "pad_list",
|
||||
"data_format": "format"
|
||||
},
|
||||
"Conv3DBackpropInputD": {
|
||||
"pads": "pad_list",
|
||||
"data_format": "format"
|
||||
},
|
||||
"Conv3DBackpropFilterD": {
|
||||
"pads": "pad_list",
|
||||
"data_format": "format"
|
||||
},
|
||||
"Conv2DTransposeD": {
|
||||
"input_size": "input_sizes",
|
||||
"strides": "stride",
|
||||
"pads": "pad_list",
|
||||
"dilations": "dilation",
|
||||
"data_format": "format"
|
||||
},
|
||||
"MaxPoolWithArgmax": {
|
||||
"ksize": "kernel_size",
|
||||
"padding": "pad_mode"
|
||||
},
|
||||
"SoftmaxGradExt": {
|
||||
"axes": "axis",
|
||||
"keep_dims": "keepdims"
|
||||
},
|
||||
"Conv2DBackpropFilterD": {
|
||||
"filter_size": "filter_sizes",
|
||||
"strides": "stride",
|
||||
"pads": "pad_list",
|
||||
"dilations": "dilation",
|
||||
"data_format": "format"
|
||||
},
|
||||
"Conv2DBackpropInputD": {
|
||||
"input_size": "input_sizes",
|
||||
"strides": "stride",
|
||||
"pads": "pad_list",
|
||||
"dilations": "dilation",
|
||||
"data_format": "format"
|
||||
},
|
||||
"Conv2DBackpropFilter": {
|
||||
"strides": "stride",
|
||||
"pads": "pad_list",
|
||||
"dilations": "dilation",
|
||||
"data_format": "format"
|
||||
},
|
||||
"Conv2DBackpropInput": {
|
||||
"strides": "stride",
|
||||
"pads": "pad_list",
|
||||
"dilations": "dilation",
|
||||
"data_format": "format"
|
||||
},
|
||||
"ConcatD": {
|
||||
"concat_dim": "axis"
|
||||
},
|
||||
"DepthwiseConv2D": {
|
||||
"strides": "stride",
|
||||
"dilations": "dilation",
|
||||
"pads": "pad_list",
|
||||
"data_format": "format",
|
||||
"offfset_x": "offset_a"
|
||||
},
|
||||
"ExtractVolumePatches": {
|
||||
"ksizes": "kernel_size"
|
||||
},
|
||||
"L2Normalize": {
|
||||
"eps": "epsilon"
|
||||
},
|
||||
"L2NormalizeGrad": {
|
||||
"dim": "axis",
|
||||
"eps": "epsilon"
|
||||
},
|
||||
"MaxPoolGradWithArgmax": {
|
||||
"ksize": "kernel_size",
|
||||
"padding": "pad_mode"
|
||||
},
|
||||
"BiasAddGrad": {
|
||||
"data_format": "format"
|
||||
},
|
||||
"FusedDbnDw": {
|
||||
"filter_size": "filter_sizes",
|
||||
"strides": "stride",
|
||||
"pads": "pad_list",
|
||||
"dilations": "dilation",
|
||||
"data_format": "format"
|
||||
},
|
||||
"MaxPool": {
|
||||
"ksize": "kernel_size",
|
||||
"padding": "pad_mode",
|
||||
"data_format": "format"
|
||||
},
|
||||
"ReduceMeanD": {
|
||||
"axes": "axis"
|
||||
},
|
||||
"ReduceSumD": {
|
||||
"axes": "axis"
|
||||
},
|
||||
"ReduceAnyD": {
|
||||
"axes": "axis"
|
||||
},
|
||||
"ReduceMaxD": {
|
||||
"axes": "axis"
|
||||
},
|
||||
"ReduceMinD": {
|
||||
"axes": "axis"
|
||||
},
|
||||
"ReduceAllD": {
|
||||
"axes": "axis"
|
||||
},
|
||||
"ReduceProdD": {
|
||||
"axes": "axis"
|
||||
},
|
||||
"ReduceStd": {
|
||||
"dim": "axis",
|
||||
"keepdim": "keep_dims"
|
||||
},
|
||||
"SoftmaxV2": {
|
||||
"axes": "axis"
|
||||
},
|
||||
"LogSoftmaxV2": {
|
||||
"axes": "axis"
|
||||
},
|
||||
"ArgMaxD": {
|
||||
"dimension": "axis"
|
||||
},
|
||||
"BatchMatMul": {
|
||||
"adj_x1": "transpose_x1",
|
||||
"adj_x2": "transpose_x2"
|
||||
},
|
||||
"BatchMatMulV2": {
|
||||
"adj_x1": "transpose_x1",
|
||||
"adj_x2": "transpose_x2"
|
||||
},
|
||||
"BatchNormal": {
|
||||
"data_format": "format"
|
||||
},
|
||||
"ArgMaxWithValue": {
|
||||
"dimension": "axis"
|
||||
},
|
||||
"SplitD": {
|
||||
"split_dim": "axis",
|
||||
"num_split": "output_num"
|
||||
},
|
||||
"BiasAdd": {
|
||||
"data_format": "format"
|
||||
},
|
||||
"SliceD": {
|
||||
"offsets": "begin"
|
||||
},
|
||||
"MaxPoolGrad": {
|
||||
"ksize": "kernel_size",
|
||||
"padding": "pad_mode",
|
||||
"data_format": "format"
|
||||
},
|
||||
"MaxPool3D": {
|
||||
"ksize": "kernel_size",
|
||||
"padding": "pad_mode",
|
||||
"pads": "pad_list",
|
||||
"data_format": "format"
|
||||
},
|
||||
"MaxPool3DGrad": {
|
||||
"ksize": "kernel_size",
|
||||
"padding": "pad_mode",
|
||||
"pads": "pad_list",
|
||||
"data_format": "format"
|
||||
},
|
||||
"MaxPoolGradGrad": {
|
||||
"ksize": "kernel_size",
|
||||
"padding": "pad_mode",
|
||||
"data_format": "format"
|
||||
},
|
||||
"AvgPool": {
|
||||
"ksize": "kernel_size",
|
||||
"padding": "pad_mode",
|
||||
"data_format": "format"
|
||||
},
|
||||
"BatchNorm": {
|
||||
"data_format": "format"
|
||||
},
|
||||
"BatchNormGrad": {
|
||||
"data_format": "format"
|
||||
},
|
||||
"ArgMin": {
|
||||
"dimension": "axis"
|
||||
},
|
||||
"ArgMinD": {
|
||||
"dimension": "axis"
|
||||
},
|
||||
"LpNorm": {
|
||||
"axes": "axis",
|
||||
"keepdim": "keep_dims"
|
||||
},
|
||||
"SmoothL1LossV2": {
|
||||
"sigma": "beta"
|
||||
},
|
||||
"Roll": {
|
||||
"shifts": "shift",
|
||||
"dims": "axis"
|
||||
},
|
||||
"SmoothL1LossGradV2": {
|
||||
"sigma": "beta"
|
||||
},
|
||||
"Centralization": {
|
||||
"axes": "axis"
|
||||
},
|
||||
"MaxPool3DGradGradD": {
|
||||
"ksize": "kernel_size"
|
||||
}
|
||||
},
|
||||
"AttrDefaultValue": {
|
||||
"Log": {
|
||||
"base": "-1.0",
|
||||
"scale": "1.0",
|
||||
"shift": "0.0"
|
||||
},
|
||||
"ScatterNdUpdate": {
|
||||
"use_locking": "false"
|
||||
},
|
||||
"OneHotD": {
|
||||
"axis": "-1"
|
||||
},
|
||||
"Iou": {
|
||||
"mode": "iou",
|
||||
"eps": "1.0"
|
||||
},
|
||||
"GatherV2D": {
|
||||
"axis": "-1"
|
||||
},
|
||||
"MaxPoolGrad": {
|
||||
"data_format": "NHWC"
|
||||
},
|
||||
"ResizeNearestNeighborV2D": {
|
||||
"align_corners": "false",
|
||||
"half_pixel_centers": "false"
|
||||
},
|
||||
"ResizeNearestNeighborV2GradD": {
|
||||
"align_corners": "false",
|
||||
"half_pixel_centers": "false"
|
||||
},
|
||||
"MaxPool3D": {
|
||||
"pads": "0,0,0",
|
||||
"dilation": "1,1,1",
|
||||
"ceil_mode": "0"
|
||||
}
|
||||
},
|
||||
"InputOrders": {
|
||||
"LogSoftmaxGrad": [1, 0],
|
||||
"LayerNormGrad": [1, 0, 2, 3, 4],
|
||||
"LayerNormBetaGammaBackprop": [1, 0, 2, 3],
|
||||
"LayerNormXBackprop": [1, 0, 2, 3, 4],
|
||||
"LayerNormXBackpropV2": [1, 0, 2, 3, 4],
|
||||
"ApplyCenteredRMSPropD": [0, 1, 2, 3, 5, 6, 7, 8, 4],
|
||||
"Conv2DBackpropInputD": [1, 0],
|
||||
"Conv2DBackpropFilterD": [1, 0],
|
||||
"MinimumGrad": [2, 0, 1],
|
||||
"MaximumGrad": [2, 0, 1],
|
||||
"StridedSliceGrad": [1, 2, 3, 4, 0],
|
||||
"Conv2DBackpropInput": [2, 1, 0],
|
||||
"Conv2DBackpropFilter": [1, 2, 0],
|
||||
"FusionOp_Conv2DBackpropInputD_AddN_ReluGradV2": [1, 0, 2, 3],
|
||||
"FusionOp_Conv2DBackpropInputD_ReluGradV2": [1, 0, 2]
|
||||
},
|
||||
"SkipDynamicCompileStatic": ["SoftmaxV2", "PRelu", "Trunc", "AccumulateNV2",
|
||||
"SoftmaxCrossEntropyWithLogits", "ReduceMeanD", "SquareSumV1", "BiasAddGrad"],
|
||||
# BroadcastTo: The name is occupied
|
||||
# DynamicBroadcastTo: The name is occupied
|
||||
# BatchToSpaceD: attr type is listInt，not listListInt
|
||||
# BatchToSpaceNDD: attr type is listInt，not listListInt
|
||||
# SpaceToBatchD: attr type is listInt，not listListInt
|
||||
# SpaceToBatchNDD: attr type is listInt，not listListInt
|
||||
# DynamicGRUV2: input4 is None, GE will change to hidden op by pass
|
||||
# DynamicRNN: input4 is None, GE will change to hidden op by pass
|
||||
# KLDivLossGrad: Accuracy issues
|
||||
# ScatterNdUpdate: not support int8 in op json
|
||||
# ScatterNdAdd: not support int8 in op json
|
||||
# UnsortedSegmentSum: check support failed when shape is -2
|
||||
# ConcatOffset: Hadn't adapted tbe implementation
|
||||
# MirrorPad: Hadn't adapted tbe implementation
|
||||
# InplaceIndexAdd: check support failed if var has only one dimension
|
||||
# Expand: Hadn't adapted tbe implementation
|
||||
# ExpandD: Hadn't adapted tbe implementation
|
||||
# Cross: Hadn't adapted tbe implementation
|
||||
# LinSpaceD: Hadn't adapted tbe implementation
|
||||
# Cast: Accuracy issues
|
||||
# AvgPool3DGradD second device format is facz_3d, but in json, the key is ndhwc
|
||||
# DataFormatDimMap: attr order swap
|
||||
# DepthwiseConv2D: Accuracy issues(second format is error in python)
|
||||
# ACos: dynamic impl errpr
|
||||
# TransData: support boll
|
||||
# ScatterNdD: Accuracy issues
|
||||
# Trace: Hadn't adapted tbe implementation
|
||||
"SkipNodes": ["BroadcastTo", "DynamicBroadcastTo", "BatchToSpaceD", "BatchToSpaceNDD", "SpaceToBatchD",
|
||||
"SpaceToBatchNDD", "DynamicGRUV2", "DynamicRNN", "KLDivLossGrad", "ScatterNdUpdate", "ScatterNdAdd",
|
||||
"ConcatOffset", "MirrorPad", "InplaceIndexAdd", "Expand", "ExpandD", "Cross", "LinSpaceD", "Cast",
|
||||
"AvgPool3DGradD", "DataFormatDimMap", "DepthwiseConv2D", "Trace", "ACos", "TransData", "ScatterNdD"]
|
||||
}
|
||||
|
||||
|
||||
@load_super_bar_config(super_bar_config)
|
||||
def _call_super_bar_config():
|
||||
"""super bar config register"""
|
||||
return
|
||||
Loading…
Reference in New Issue