!17179 some supplement of Tile operator.

From: @shen_jingxing
Reviewed-by: 
Signed-off-by:

mindspore/core/abstract/infer_functions.h

@@ -252,8 +252,6 @@ AbstractBasePtr InferImplLinSpace(const AnalysisEnginePtr &, const PrimitivePtr
                                   const AbstractBasePtrList &args_spec_list);
 AbstractBasePtr InferImplExpandDims(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
                                     const AbstractBasePtrList &args_spec_list);
-AbstractBasePtr InferImplTile(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
-                              const AbstractBasePtrList &args_spec_list);
 AbstractBasePtr InferImplGpuConvertToDynamicShape(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
                                                   const AbstractBasePtrList &args_spec_list);
 AbstractBasePtr InferImplPad(const AnalysisEnginePtr &, const PrimitivePtr &primitive,

mindspore/core/abstract/prim_arrays.cc

@@ -82,39 +82,6 @@ AbstractBasePtr InferImplBroadCastShape(const AnalysisEnginePtr &, const Primiti
   return std::make_shared<AbstractTuple>(elems);
 }
 
-AbstractBasePtr InferImplTile(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
-                              const AbstractBasePtrList &args_spec_list) {
-  // Inputs: a tensor and a tuple.
-  const std::string op_name = primitive->name();
-  CheckArgsSize(op_name, args_spec_list, 2);
-  auto arg = CheckArg<AbstractTensor>(op_name, args_spec_list, 0);
-  auto multiples = CheckArg<AbstractTuple>(op_name, args_spec_list, 1);
-
-  ShapePtr input_shape = arg->shape();
-  (void)CheckTensorDType(arg, {kInt16, kFloat16, kInt32, kFloat32}, "Input 0 of Tile should be %s");
-
-  auto mul_shp_value = multiples->BuildValue();
-  if (mul_shp_value->isa<AnyValue>()) {
-    MS_LOG(EXCEPTION) << "shape's data field can't be anything: " << args_spec_list[1]->ToString();
-  }
-
-  ShapeVector mul_shp;
-  auto value_tuple_mul = mul_shp_value->cast<ValueTuplePtr>();
-  auto mul_shp_data = value_tuple_mul->value();
-  (void)std::transform(std::begin(mul_shp_data), std::end(mul_shp_data), std::back_inserter(mul_shp),
-                       [](const ValuePtr &e) -> int64_t { return GetValue<int64_t>(e); });
-  if (input_shape->shape().size() != mul_shp_data.size()) {
-    MS_LOG(EXCEPTION) << "Tile requires input and multiples size equal, while the input size is "
-                      << input_shape->shape().size() << ", value size is: " << mul_shp_data.size() << ".";
-  }
-
-  ShapeVector result_shp;
-  for (size_t i = 0; i < mul_shp_data.size(); ++i) {
-    result_shp.push_back(input_shape->shape()[i] * mul_shp[i]);
-  }
-  return std::make_shared<AbstractTensor>(arg->element(), std::make_shared<Shape>(result_shp));
-}
-
 AbstractBasePtr InferImplStack(const AnalysisEnginePtr &, const PrimitivePtr &primitive,
                                const AbstractBasePtrList &args_spec_list) {
   // Inputs: a tuple of tensor.

mindspore/core/abstract/primitive_infer_map.cc

@@ -25,6 +25,7 @@
 #include "ops/add.h"
 #include "abstract/abstract_function.h"
 #include "abstract/infer_functions.h"
+#include "ops/tile.h"
 
 namespace mindspore {
 namespace abstract {
@@ -174,7 +175,7 @@ PrimitiveEvalImplMap &GetPrimitiveToBackendEvalImplMap() {
     {prim::kPrimSqrtGrad, {InferImplSqrtGrad, nullptr, true}},
     {prim::kPrimSub, {InferImplSub, nullptr, false}},
     {prim::kPrimEqual, {InferImplEqual, nullptr, true}},
-    {prim::kPrimTile, {InferImplTile, nullptr, false}},
+    {prim::kPrimTile, {ops::TileInfer, nullptr, true}},
     {prim::kPrimReduceSum, {InferImplReduceFunc, nullptr, true}},
     {prim::kPrimReduceMean, {InferImplReduceFunc, nullptr, true}},
     {prim::kPrimReduceAll, {InferImplReduceFunc, nullptr, true}},

mindspore/core/ops/tile.cc

@@ -41,6 +41,9 @@ std::vector<int64_t> GetInferShape(const std::vector<int64_t> &input_shape, cons
                                 "length of dimension in input_x";
   }
   for (size_t i = 0; i < multiples_w.size(); i++) {
+    if (infer_shape[i] == abstract::Shape::SHP_ANY) {
+      continue;
+    }
     infer_shape[i] *= multiples_w[i];
   }
   return infer_shape;