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!29290 Fix Broadcast primitive tuple input incorrect elimination. 

Merge pull request !29290 from huanghui/fix-broadcast-use-flag
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i-robot 2022-01-19 09:28:23 +00:00 committed by Gitee
parent e6f3c71520 37eaf96f93
commit d65f8e3953
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GPG Key ID: 173E9B9CA92EEF8F
4 changed files with 12 additions and 5 deletions
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1
mindspore/ccsrc/pipeline/jit/static_analysis/prim.cc
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@ -88,6 +88,7 @@ mindspore::HashSet<std::string> prims_use_sequence_elements{
prim::kPrimUniformReal->name(), prim::kPrimUniformReal->name(),
prim::kPrimSparseToDense->name(), prim::kPrimSparseToDense->name(),
prim::kPrimSparseTensorDenseMatmul->name(), prim::kPrimSparseTensorDenseMatmul->name(),
prim::kPrimBroadcast->name(),
"InvertPermutation", "InvertPermutation",
"Meshgrid", "Meshgrid",
"TransShape", "TransShape",

3
mindspore/core/abstract/prim_arrays.cc
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@ -115,7 +115,8 @@ AbstractBasePtr InferImplBroadCastShape(const AnalysisEnginePtr &, const Primiti
(void)std::transform(res.begin(), res.end(), std::back_inserter(elems), [](int64_t n) -> AbstractBasePtr { (void)std::transform(res.begin(), res.end(), std::back_inserter(elems), [](int64_t n) -> AbstractBasePtr {
return std::make_shared<AbstractScalar>(std::make_shared<Int64Imm>(n), kInt64); return std::make_shared<AbstractScalar>(std::make_shared<Int64Imm>(n), kInt64);
}); });
SetSequenceElementsUseFlags(xs, true);
SetSequenceElementsUseFlags(ys, true);
return std::make_shared<AbstractTuple>(elems); return std::make_shared<AbstractTuple>(elems);
} }

9
mindspore/core/ops/transpose.cc
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@ -94,13 +94,18 @@ AbstractBasePtr TransposeInfer(const abstract::AnalysisEnginePtr &, const Primit
const std::vector<AbstractBasePtr> &input_args) { const std::vector<AbstractBasePtr> &input_args) {
MS_EXCEPTION_IF_NULL(primitive); MS_EXCEPTION_IF_NULL(primitive);
constexpr size_t input_perm_index = 1; constexpr size_t input_perm_index = 1;
(void)CheckAndConvertUtils::CheckInteger("Transpose infer", SizeToLong(input_args.size()), kGreaterEqual, 1, // The second input is optional.
constexpr size_t input_size1 = 1;
constexpr size_t input_size2 = 2;
(void)CheckAndConvertUtils::CheckInteger("Transpose infer", SizeToLong(input_args.size()), kGreaterEqual, input_size1,
primitive->name()); primitive->name());
auto type = InferType(primitive, input_args); auto type = InferType(primitive, input_args);
auto shape = InferShape(primitive, input_args); auto shape = InferShape(primitive, input_args);
auto res = abstract::MakeAbstract(shape, type); auto res = abstract::MakeAbstract(shape, type);
// Set all used flags of tuple as true. if (input_args.size() == input_size2) {
SetSequenceElementsUseFlags(input_args[input_perm_index], true); SetSequenceElementsUseFlags(input_args[input_perm_index], true);
}
return res; return res;
} }
REGISTER_PRIMITIVE_EVAL_IMPL(Transpose, prim::kPrimTranspose, TransposeInfer, nullptr, true); REGISTER_PRIMITIVE_EVAL_IMPL(Transpose, prim::kPrimTranspose, TransposeInfer, nullptr, true);

2
mindspore/python/mindspore/ops/operations/comm_ops.py
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@ -526,7 +526,7 @@ class Broadcast(PrimitiveWithInfer):
group (str): The communication group to work on. Default: "GlobalComm.WORLD_COMM_GROUP". group (str): The communication group to work on. Default: "GlobalComm.WORLD_COMM_GROUP".
Inputs: Inputs:
- **input_x** (Tensor) - The shape of tensor is :math:`(x_1, x_2, ..., x_R)`. - **input_x** (tuple[Tensor]) - The shape of tensor is :math:`(x_1, x_2, ..., x_R)`.
Outputs: Outputs:
Tensor, has the same shape of the input, i.e., :math:`(x_1, x_2, ..., x_R)`. Tensor, has the same shape of the input, i.e., :math:`(x_1, x_2, ..., x_R)`.