masahi commented on a change in pull request #6232:
URL: https://github.com/apache/incubator-tvm/pull/6232#discussion_r467647626
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File path: src/relay/op/tensor/reduce.cc
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@@ -542,51 +547,61 @@ bool VarianceRel(const Array<Type>& types, int
num_inputs, const Attrs& attrs,
std::vector<IndexExpr> mean_shape(mean->shape.begin(), mean->shape.end());
CHECK_EQ(in_shape.size(), mean_shape.size());
- const ReduceAttrs* param = attrs.as<ReduceAttrs>();
+ const VarianceAttrs* param = attrs.as<VarianceAttrs>();
CHECK(param != nullptr);
// assign output type and shape
- auto oshape = ReduceShapeImpl(in_shape, param, reporter);
+ auto oshape = ReduceShapeImpl(in_shape, param->axis, param->keepdims,
param->exclude, reporter);
reporter->Assign(types[2], TensorType(oshape, data->dtype));
return true;
}
Array<te::Tensor> VarianceCompute(const Attrs& attrs, const Array<te::Tensor>&
inputs,
const Type& out_type) {
IndexExpr count = tir::make_const(inputs[0]->dtype, 1);
- const ReduceAttrs* param = attrs.as<ReduceAttrs>();
+ const VarianceAttrs* param = attrs.as<VarianceAttrs>();
CHECK(param != nullptr);
auto axes = param->axis;
+ bool unbiased = param->unbiased;
auto data = inputs[0];
auto mean = inputs[1];
for (int64_t i : GetReduceAxes(data->shape.size(), param->axis,
param->exclude)) {
count *= data->shape[i];
}
+ if (unbiased) {
+ count -= 1;
+ }
std::vector<Integer> expand_shape;
auto sq_diff = topi::power(topi::subtract(data, mean), 2);
- auto var = topi::divide(ReduceCompute(attrs, {sq_diff}, out_type,
topi::sum)[0], count);
Review comment:
If `VarianceAttrs` could inherit from `ReduceAttrs`, we don't have to
introduce this change. But again, I don't know if that inheritance of Attrs
works...
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