[res/tfl_recipes] Add REGRESS_Issue_13863 (#14064)

This commit adds REGRESS_Issue_13863 tflite recipe.

ONE-DCO-1.0-Signed-off-by: HanJin Choi [email protected]

compiler/common-artifacts/exclude.lst

@@ -125,6 +125,7 @@ tcgenerate(ReLU6_dynamic_000) # TestDataGenerator does not support unknown dimen
 tcgenerate(ReLUN1To1_000)
 tcgenerate(ReLUN1To1_dynamic_000) # TestDataGenerator does not support unknown dimension
 tcgenerate(Reshape_003) # luci-interpreter doesn't support reshape without built-in option
+tcgenerate(Reshape_004) # has 0 in shape
 tcgenerate(ReverseSequence_000)
 tcgenerate(ReverseV2_000)
 tcgenerate(Round_000)

compiler/luci/import/src/ImporterEx.cpp

@@ -25,6 +25,14 @@
 namespace luci
 {
 
+namespace
+{
+
+// limitation of current flatbuffers file size
+inline constexpr uint64_t FLATBUFFERS_SIZE_MAX = 2147483648UL; // 2GB
+
+} // namespace
+
 std::unique_ptr<Module> ImporterEx::importVerifyModule(const std::string &input_path) const
 {
   foder::FileLoader file_loader{input_path};
@@ -43,11 +51,14 @@ std::unique_ptr<Module> ImporterEx::importVerifyModule(const std::string &input_
   auto data_data = reinterpret_cast<uint8_t *>(model_data.data());
   auto data_size = model_data.size();
 
-  flatbuffers::Verifier verifier{data_data, data_size};
-  if (!circle::VerifyModelBuffer(verifier))
+  if (data_size < FLATBUFFERS_SIZE_MAX)
   {
-    std::cerr << "ERROR: Invalid input file '" << input_path << "'" << std::endl;
-    return nullptr;
+    flatbuffers::Verifier verifier{data_data, data_size};
+    if (!circle::VerifyModelBuffer(verifier))
+    {
+      std::cerr << "ERROR: Invalid input file '" << input_path << "'" << std::endl;
+      return nullptr;
+    }
   }
 
   Importer importer(_source);

compiler/luci/service/src/Nodes/CircleReshape.cpp

@@ -82,15 +82,32 @@ loco::TensorShape Algorithm::visit(const luci::CircleReshape *node)
     {
       LUCI_ASSERT(const_shape_node->dtype() == S32, "Only support int32 CircleConst");
 
+      // NOTE for rank(shape_by_input before) < rank(shape_by_input after),
+      //      shape_by_input after will be filled with unknown dims
       shape_by_input.rank(const_shape_node->size<S32>());
 
       for (uint32_t axis = 0; axis < shape_by_input.rank(); ++axis)
       {
-        shape_by_input.dim(axis) = const_shape_node->at<S32>(axis);
         if (const_shape_node->at<S32>(axis) < 0)
         {
           shape_by_input.dim(axis).unset();
         }
+        else if (const_shape_node->at<S32>(axis) == 0)
+        {
+          const auto node_tensor = loco::must_cast<luci::CircleNode *>(node->tensor());
+          // set dim value to input
+          if (node_tensor->shape_status() == luci::ShapeStatus::VALID && axis < node_tensor->rank())
+            shape_by_input.dim(axis) = node_tensor->dim(axis);
+          else
+            shape_by_input.dim(axis).set(0);
+          // TODO allow 0 from ONNX
+        }
+        else
+        {
+          shape_by_input.dim(axis).set(const_shape_node->at<S32>(axis));
+        }
+        // check valid or stop for debugging
+        assert(shape_by_input.dim(axis).value() > 0 || !shape_by_input.dim(axis).known());
       }
     }
     else
@@ -148,14 +165,27 @@ loco::TensorShape Algorithm::visit(const luci::CircleReshape *node)
   }
   for (uint32_t dim_index = 0; dim_index < output_shape.rank(); ++dim_index)
   {
-    const uint32_t dim_value = output_shape.dim(dim_index).value();
+    uint32_t dim_value = output_shape.dim(dim_index).value();
     if (not output_shape.dim(dim_index).known())
     {
       LUCI_ASSERT(unknown_dim_index == UINT32_MAX, "More than one unknown dimension");
       unknown_dim_index = dim_index;
     }
     else
     {
+      if (!dim_value)
+      {
+        // refer https://github.com/Samsung/ONE/issues/14074#issuecomment-2370795003
+        // set dim value to follow input
+        if (dim_index < input_shape.rank())
+          dim_value = input_shape.dim(dim_index).value();
+        else
+        {
+          // stop to check if this case exist for debugging
+          assert(dim_index < input_shape.rank());
+          dim_value = 1;
+        }
+      }
       output_element_count *= dim_value;
     }
   }

compiler/luci/tests/test.lst

@@ -142,6 +142,7 @@ addread(Reshape_000)
 addread(Reshape_001)
 addread(Reshape_002)
 #addread(Reshape_003) # no input, no option is not supported
+addread(Reshape_004)
 addread(Reshape_U8_000)
 addread(ResizeBilinear_000)
 addread(ResizeBilinear_U8_000)
@@ -374,6 +375,7 @@ addwrite(Reshape_000)
 addwrite(Reshape_001)
 addwrite(Reshape_002)
 #addwrite(Reshape_003) # no input, no option is not supported
+addwrite(Reshape_004)
 addwrite(Reshape_U8_000)
 addwrite(ResizeBilinear_000)
 addwrite(ResizeBilinear_U8_000)

res/TensorFlowLiteRecipes/Reshape_004/test.recipe

@@ -0,0 +1,31 @@
+# NOTE test model for 0 in shape.
+# May not work in interpreter.
+operand {
+  name: "ifm"
+  type: FLOAT32
+  shape { dim: 1 dim: 3 dim: 2 dim: 3 }
+}
+operand {
+  name: "shape"
+  type: INT32
+  shape { dim: 3 }
+  filler { tag: "explicit" arg: "0" arg: "3" arg: "-1" }
+}
+operand {
+  name: "ofm"
+  type: FLOAT32
+  shape { dim: 1 dim: 3 dim: 6 }
+}
+operation {
+  type: "Reshape"
+  reshape_options {
+    new_shape: 0
+    new_shape: 3
+    new_shape: -1
+  }
+  input: "ifm"
+  input: "shape"
+  output: "ofm"
+}
+input: "ifm"
+output: "ofm"