Imported Upstream version 0.3upstream/0.3

1 files changed, 106 insertions, 0 deletions

diff --git a/libs/tflite/src/ext/nnapi_delegate_ex_AddOpsAndParams_lambda.inc b/libs/tflite/src/ext/nnapi_delegate_ex_AddOpsAndParams_lambda.inc
new file mode 100644
index 000000000..a91e4de60
--- /dev/null
+++ b/libs/tflite/src/ext/nnapi_delegate_ex_AddOpsAndParams_lambda.inc
@@ -0,0 +1,106 @@
+// This file is included from AddOpsAndParams defined in nnapi_delegate.cc
+// and contains lambda for extened implementation to original Tensorflow Lite.
+    auto add_resize_bilinear_params = [&add_scalar_int32, &interpreter, &augmented_inputs](void* data) {
+      auto builtin = reinterpret_cast<TfLiteResizeBilinearParams*>(data);
+      if  (builtin->align_corners) {
+        FATAL("Resize bilinear does not support align corners in NNAPI");
+      }
+
+      TfLiteTensor* tensor = interpreter->tensor(augmented_inputs.back());
+      assert(tensor->type == kTfLiteInt32);
+      assert(tensor->bytes == sizeof(int)*2);
+      augmented_inputs.pop_back();
+
+      int height = ((int*)(tensor->data.raw))[1];
+      int width = ((int*)(tensor->data.raw))[0];
+      add_scalar_int32(height);
+      add_scalar_int32(width);
+    };
+
+    auto check_l2normalization_params = [interpreter, &node](void* data) {
+      auto builtin = reinterpret_cast<TfLiteL2NormParams*>(data);
+      if (builtin->activation != kTfLiteActNone) {
+        FATAL("NNAPI does not support L2Normalization with fused activations");
+      }
+      if ((node.inputs->size > 0) &&
+            (interpreter->tensor(node.inputs->data[0])->dims->size != 4)) {
+          FATAL("NNAPI only supports input rank 4 for L2Normalization");
+      }
+    };
+
+    auto add_transpose_conv_params = [&add_scalar_int32](void* data) {
+      auto builtin = reinterpret_cast<TfLiteTransposeConvParams*>(data);
+      add_scalar_int32(builtin->padding);
+      add_scalar_int32(builtin->stride_width);
+      add_scalar_int32(builtin->stride_height);
+    };
+
+    auto add_lrn_params = [&add_scalar_int32,
+                            &add_scalar_float32](void* data) {
+      auto builtin = reinterpret_cast<TfLiteLocalResponseNormParams*>(data);
+      add_scalar_int32(builtin->radius);
+      add_scalar_float32(builtin->bias);
+      add_scalar_float32(builtin->alpha);
+      add_scalar_float32(builtin->beta);
+    };
+
+    auto add_strided_slice_params = [&add_scalar_int32](void* data) {
+      auto builtin = reinterpret_cast<TfLiteStridedSliceParams*>(data);
+      add_scalar_int32(builtin->begin_mask);
+      add_scalar_int32(builtin->end_mask);
+      // ellipsis_mask and new_axis_mask are not supported on nn runtime
+      // cf) tflite interpreter supports both operations
+      if (builtin->ellipsis_mask) {
+        FATAL("STRIDE_SLICE does not support ellipsis_mask in NNAPI");
+      }
+      if (builtin->new_axis_mask) {
+        FATAL("STRIDE_SLICE does not support new_axis_mask in NNAPI");
+      }
+      add_scalar_int32(builtin->shrink_axis_mask);
+    };
+
+    auto add_gather_ex_params = [&add_scalar_int32](void* data) {
+      auto builtin = reinterpret_cast<TfLiteGatherParams*>(data);
+      add_scalar_int32(builtin->axis);
+      if (builtin->axis != 0) {
+        FATAL("GATHER does not support axis>0 in NNAPI");
+      }
+    };
+
+#ifndef OBS_BUILD
+    auto add_pack_ex_params = [&add_scalar_int32](void* data) {
+      auto builtin = reinterpret_cast<TfLitePackParams*>(data);
+      add_scalar_int32(builtin->values_count);
+      add_scalar_int32(builtin->axis);
+    };
+
+    auto add_unpack_ex_params = [&add_scalar_int32](void* data) {
+      auto builtin = reinterpret_cast<TfLiteUnpackParams*>(data);
+      add_scalar_int32(builtin->num);
+      add_scalar_int32(builtin->axis);
+    };
+#endif
+
+    auto check_batch_to_space_params = [interpreter, &node, &augmented_inputs]() {
+
+    //If there are 3 inputs, check if crops is having default values {0, 0, 0, 0}
+    //Else unsupported by NNAPI
+
+      if(augmented_inputs.size() == 3)
+      {
+        const uint32_t crops_buffer_index = node.inputs->data[2];
+        const TfLiteTensor* crops = interpreter->tensor(crops_buffer_index);
+        const int *crops_value = crops->data.i32;
+
+        //Check if crops is having default values {0, 0, 0, 0}
+        if(crops_value[0] != 0 || crops_value[1] != 0 || crops_value[2] != 0 || crops_value[3] != 0)
+        {
+          FATAL("BATCH_TO_SPACE_ND does not support Explicit crops in NNAPI");
+        }
+        else
+        {
+          //Restrict crops input and pass only other two inputs
+          augmented_inputs.pop_back();
+        }
+      }
+    };