Add fixed_channel and few_channel mode to int8 in generator (#829)
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@ -527,6 +527,8 @@ def CreateConv2dFixedChannelsOperator(manifest, layout, tile_descriptions, data_
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manifest.append(new_operation)
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operations.append(new_operation)
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return operations
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# Convolution for 2D operations specialized for few channels
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def CreateConv2dFewChannelsOperator(manifest, layout, tile_descriptions, data_type, channel_counts, \
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@ -571,6 +573,8 @@ def CreateConv2dFewChannelsOperator(manifest, layout, tile_descriptions, data_ty
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manifest.append(new_operation)
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operations.append(new_operation)
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return operations
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# Convolution for 3D operations
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def CreateConv3dOperator(manifest, layout, tile_descriptions, data_type, alignment, \
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conv_kinds = [ConvKind.Fprop, ConvKind.Dgrad, ConvKind.Wgrad], epilogue_functor = EpilogueFunctor.LinearCombination):
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@ -1467,6 +1471,10 @@ def GenerateSM75_TensorOp_8816_TN(manifest, cuda_version):
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operations += CreateConv2dOperator(manifest, conv_layout, tile_descriptions,
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data_type_mixed, alignment_constraints, [ConvKind.Fprop], EpilogueFunctor.LinearCombinationClamp)
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operations += CreateConv2dFixedChannelsOperator(manifest, conv_layout, tile_descriptions,
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data_type_mixed, [4, 8, 16], [ConvKind.Fprop], EpilogueFunctor.LinearCombinationClamp)
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operations += CreateConv2dFewChannelsOperator(manifest, conv_layout, tile_descriptions,
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data_type_mixed, [4, 8, 16], [ConvKind.Fprop], EpilogueFunctor.LinearCombinationClamp)
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for op in operations:
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if op.tile_description.threadblock_shape[1] >= 128:
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