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[RELAY] Refactor FoldConstant to skip TNonComputationalOps #6720

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merged 12 commits into from
Oct 24, 2020
Merged

[RELAY] Refactor FoldConstant to skip TNonComputationalOps #6720

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3b7cda0
add TNonComputational to qnn ops and change FoldConstant
electriclilies Oct 20, 2020
064b270
remove comments
electriclilies Oct 20, 2020
bed3228
merge main
electriclilies Oct 20, 2020
4d983a9
check if op in nonComputational map
electriclilies Oct 20, 2020
de60928
forgot to mark device_copy op as TNonComputational
electriclilies Oct 21, 2020
b1ff6ff
hacky fix to fuseops pass
electriclilies Oct 21, 2020
c4f7942
fix typo
electriclilies Oct 21, 2020
68150e2
manually skip device_copy in fold_constant
electriclilies Oct 21, 2020
c0492ff
Merge remote-tracking branch 'upstream/main' into non-computational
electriclilies Oct 22, 2020
2653ecd
Update src/relay/transforms/fold_constant.cc
Oct 22, 2020
9f518f7
Merge remote-tracking branch 'upstream/main' into non-computational
electriclilies Oct 23, 2020
58d3af0
Merge branch 'non-computational' of github.com:electriclilies/incubat…
electriclilies Oct 23, 2020
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1 change: 1 addition & 0 deletions src/relay/qnn/op/concatenate.cc
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Expand Up @@ -207,6 +207,7 @@ RELAY_REGISTER_OP("qnn.concatenate")
"The quantization zero_point of the output tensor.")
.set_support_level(11)
.add_type_rel("QnnConcatenate", QnnConcatenateRel)
.set_attr<TNonComputational>("TNonComputational", true)
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.set_attr<FTVMLegalize>("FTVMQnnCanonicalize", ConcatenateQnnCanonicalize)
.set_attr<FInferCorrectLayout>("FInferCorrectLayout", QnnConcatenateLayout);

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1 change: 1 addition & 0 deletions src/relay/qnn/op/convolution.cc
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Expand Up @@ -733,6 +733,7 @@ operator to understand how to scale back the int32 output to (u)int8.
"The quantization zero_point of the weight tensor.")
.set_support_level(11)
.add_type_rel("QnnConv2D", QnnConv2DRel)
.set_attr<TNonComputational>("TNonComputational", true)
.set_attr<FTVMLegalize>("FTVMQnnCanonicalize", QnnConv2DCanonicalize)
.set_attr<FInferCorrectLayout>("FInferCorrectLayout", QnnConvInferCorrectLayout);

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1 change: 1 addition & 0 deletions src/relay/qnn/op/dense.cc
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Expand Up @@ -189,6 +189,7 @@ RELAY_REGISTER_OP("qnn.dense")
"The quantization zero_point of the weight tensor.")
.set_support_level(11)
.add_type_rel("QDense", QnnDenseRel)
.set_attr<TNonComputational>("TNonComputational", true)
.set_attr<FTVMLegalize>("FTVMQnnCanonicalize", QnnDenseCanonicalize);

TVM_REGISTER_GLOBAL("relay.qnn.op._make.dense").set_body_typed(MakeQuantizedDense);
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1 change: 1 addition & 0 deletions src/relay/qnn/op/dequantize.cc
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Expand Up @@ -136,6 +136,7 @@ The input is always quantized (int8, uint8) and will be converted to float32 giv
.add_argument("input_zero_point", "Tensor", "The quantization zero_point of the input tensor.")
.set_support_level(11)
.add_type_rel("Dequantize", DequantizeRel)
.set_attr<TNonComputational>("TNonComputational", true)
.set_attr<FTVMLegalize>("FTVMQnnCanonicalize", DequantizeQnnCanonicalize);

TVM_REGISTER_GLOBAL("relay.qnn.op._make.dequantize").set_body_typed(MakeDequantize);
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1 change: 1 addition & 0 deletions src/relay/qnn/op/op_common.h
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Expand Up @@ -215,6 +215,7 @@ static inline bool QnnBroadcastRel(const Array<Type>& types, int num_inputs, con
.add_argument("output_scale", "Tensor", "The scale of the output tensor.") \
.add_argument("output_zero_point", "Tensor", "The zero_point of the output tensor.") \
.add_type_rel("QnnBroadcast", QnnBroadcastRel) \
.set_attr<TNonComputational>("TNonComputational", true) \
.set_attr<FInferCorrectLayout>("FInferCorrectLayout", QnnBinaryBroadcastLayout)

} // namespace qnn
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1 change: 1 addition & 0 deletions src/relay/qnn/op/quantize.cc
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Expand Up @@ -150,6 +150,7 @@ scale and zero point.
"The quantization zero_point of the output tensor.")
.set_support_level(11)
.add_type_rel("Quantize", QuantizeRel)
.set_attr<TNonComputational>("TNonComputational", true)
.set_attr<FTVMLegalize>("FTVMQnnCanonicalize", QuantizeQnnCanonicalize);

TVM_REGISTER_GLOBAL("relay.qnn.op._make.quantize").set_body_typed(MakeQuantize);
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1 change: 1 addition & 0 deletions src/relay/qnn/op/requantize.cc
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Expand Up @@ -324,6 +324,7 @@ Q_output = zp_output + (scale_input)/(scale_output) * (Q_input - zp_input)
"The quantization zero_point of the output tensor.")
.set_support_level(11)
.add_type_rel("Requantize", RequantizeRel)
.set_attr<TNonComputational>("TNonComputational", true)
.set_attr<FTVMLegalize>("FTVMQnnCanonicalize", RequantizeQnnCanonicalize)
.set_attr<FInferCorrectLayout>("FInferCorrectLayout", RequantizeInferCorrectLayout);

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11 changes: 8 additions & 3 deletions src/relay/transforms/fold_constant.cc
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Expand Up @@ -151,9 +151,14 @@ class ConstantFolder : public MixedModeMutator {
}

// We should think about potentially constant evaluation over these ops too.
if (call->op == invoke_tvm_op_ || call->op == shape_func_op_ || call->op == alloc_tensor_op_ ||
call->op == alloc_storage_op_ || call->op == device_copy_op_) {
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return GetRef<Call>(call);
static auto nonComputational = Op::GetAttrMap<TNonComputational>("TNonComputational");
if (auto call_node = call->op.as<OpNode>()) {
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Op op = GetRef<Op>(call_node);
if (nonComputational.count(op)) {
if (nonComputational[op]) {
return GetRef<Call>(call);
}
}
}

bool all_const_args = true;
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