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Subject [GitHub] [incubator-tvm] mbaret opened a new pull request #5100: [DRAFT][BYOC] Add support for multiple outputs to the graph partitioning flow
Date Thu, 19 Mar 2020 14:55:18 GMT
mbaret opened a new pull request #5100: [DRAFT][BYOC] Add support for multiple outputs to the
graph partitioning flow
URL: https://github.com/apache/incubator-tvm/pull/5100
 
 
   This PR makes changes to the GraphPartition pass to support producing functions with multiple
outputs as well as introducing a new pass, MergeSupported, to handle the merging of supported
operators into legal partitions.
   
   It is only a draft to demonstrate the progress we are making in this area. Our goal is
to implement the design described in the RFC here: (). We will contribute these components
as separate PRs once the design has been agreed upon.
   
   To illustrate what happens, here is a graph before and after the partitioning flow ('add'
is supported by the 'test' target, whereas 'subtract' is not):
   
   ```
   def @main(%in_1: Tensor[(10, 10), float32], %in_2: Tensor[(10, 10), float32], %in_3: Tensor[(10,
10), float32], %in_4: Tensor[(10, 10), float32], %in_5: Tensor[(10, 10), float32], %in_6:
Tensor[(10, 10), float32], %in_7: Tensor[(10, 10), float32], %in_8: Tensor[(10, 10), float32],
%in_9: Tensor[(10, 10), float32], %in_10: Tensor[(10, 10), float32]) -> Tensor[(10, 10),
float32] {
     %0 = add(%in_1, %in_2) /* ty=Tensor[(10, 10), float32] */;
     %1 = add(%in_3, %in_4) /* ty=Tensor[(10, 10), float32] */;
     %2 = add(%0, %1) /* ty=Tensor[(10, 10), float32] */;
     %3 = subtract(%in_5, %in_6) /* ty=Tensor[(10, 10), float32] */;
     %4 = subtract(%in_7, %3) /* ty=Tensor[(10, 10), float32] */;
     %5 = add(%2, %4) /* ty=Tensor[(10, 10), float32] */;
     %6 = subtract(%in_8, %5) /* ty=Tensor[(10, 10), float32] */;
     %7 = add(%in_9, %5) /* ty=Tensor[(10, 10), float32] */;
     %8 = add(%6, %7) /* ty=Tensor[(10, 10), float32] */;
     add(%in_10, %8) /* ty=Tensor[(10, 10), float32] */
   }
   ```
   
   ```
   def @test_4(%test_4_i5: Tensor[(10, 10), float32], %test_4_i0: Tensor[(10, 10), float32],
%test_4_i1: Tensor[(10, 10), float32], %test_4_i2: Tensor[(10, 10), float32], %test_4_i3:
Tensor[(10, 10), float32], %test_4_i4: Tensor[(10, 10), float32], Inline=1, Compiler="test",
ExternalSymbol="test_4", Primitive=1) -> (Tensor[(10, 10), float32], Tensor[(10, 10), float32])
{
     %0 = add(%test_4_i0, %test_4_i1) /* ty=Tensor[(10, 10), float32] */;
     %1 = add(%test_4_i2, %test_4_i3) /* ty=Tensor[(10, 10), float32] */;
     %2 = add(%0, %1) /* ty=Tensor[(10, 10), float32] */;
     %3 = add(%2, %test_4_i4) /* ty=Tensor[(10, 10), float32] */;
     %4 = add(%test_4_i5, %3) /* ty=Tensor[(10, 10), float32] */;
     (%4, %3)
   }
   
   def @default_1(%default_1_i0: Tensor[(10, 10), float32], %default_1_i1: Tensor[(10, 10),
float32], Inline=1, Compiler="default", ExternalSymbol="default_1", Primitive=1) -> Tensor[(10,
10), float32] {
     subtract(%default_1_i0, %default_1_i1) /* ty=Tensor[(10, 10), float32] */
   }
   
   def @test_0(%test_0_i0: Tensor[(10, 10), float32], %test_0_i1: Tensor[(10, 10), float32],
%test_0_i2: Tensor[(10, 10), float32], Inline=1, Compiler="test", ExternalSymbol="test_0",
Primitive=1) -> Tensor[(10, 10), float32] {
     %5 = add(%test_0_i1, %test_0_i2) /* ty=Tensor[(10, 10), float32] */;
     add(%test_0_i0, %5) /* ty=Tensor[(10, 10), float32] */
   }
   
   def @default_3(%default_3_i0: Tensor[(10, 10), float32], %default_3_i1: Tensor[(10, 10),
float32], %default_3_i2: Tensor[(10, 10), float32], Inline=1, Compiler="default", ExternalSymbol="default_3",
Primitive=1) -> Tensor[(10, 10), float32] {
     %6 = subtract(%default_3_i1, %default_3_i2) /* ty=Tensor[(10, 10), float32] */;
     subtract(%default_3_i0, %6) /* ty=Tensor[(10, 10), float32] */
   }
   
   def @main(%in_1: Tensor[(10, 10), float32], %in_2: Tensor[(10, 10), float32], %in_3: Tensor[(10,
10), float32], %in_4: Tensor[(10, 10), float32], %in_5: Tensor[(10, 10), float32], %in_6:
Tensor[(10, 10), float32], %in_7: Tensor[(10, 10), float32], %in_8: Tensor[(10, 10), float32],
%in_9: Tensor[(10, 10), float32], %in_10: Tensor[(10, 10), float32]) -> Tensor[(10, 10),
float32] {
     %7 = @default_3(%in_7, %in_5, %in_6) /* ty=Tensor[(10, 10), float32] */;
     %8 = @test_4(%in_9, %in_1, %in_2, %in_3, %in_4, %7) /* ty=(Tensor[(10, 10), float32],
Tensor[(10, 10), float32]) */;
     %9 = %8.1;
     %10 = @default_1(%in_8, %9) /* ty=Tensor[(10, 10), float32] */;
     %11 = %8.0;
     @test_0(%in_10, %10, %11) /* ty=Tensor[(10, 10), float32] */
   }
   ```
   
   This is the same example as demonstrated here [https://discuss.tvm.ai/t/relay-improved-graph-partitioning-algorithm/5830
](https://discuss.tvm.ai/t/relay-improved-graph-partitioning-algorithm/5830).

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