Improve error logs when converting model with control flow. Also update the g3doc to clearly convey that 'control flow' is not currently supported.

PiperOrigin-RevId: 248773536

tensorflow/lite/g3doc/guide/faq.md

@@ -30,8 +30,16 @@ Since the number of TensorFlow Lite operations is smaller than TensorFlow's,
 some inference models may not be able to convert. For unimplemented operations,
 take a look at the question on
 [missing operators](faq.md#why-are-some-operations-not-implemented-in-tensorflow-lite).
-Unsupported operators include embeddings and LSTM/RNNs. For conversion issues
+Unsupported operators include embeddings and LSTM/RNNs. For models with
-not related to missing operations, search our
+LSTM/RNNs, you can also try the experimental API
+[OpHint](https://www.tensorflow.org/api_docs/python/tf/lite/OpHint) to convert.
+Models with control flow ops (Switch, Merge, etc) are not convertible at the
+moment, but we are working on adding support for control flow in Tensorflow
+Lite, please see
+[GitHub issues](https://github.com/tensorflow/tensorflow/issues/28485).
+
+For conversion issues not related to missing operations or control flow ops,
+search our
 [GitHub issues](https://github.com/tensorflow/tensorflow/issues?q=label%3Acomp%3Alite+)
 or file a [new one](https://github.com/tensorflow/tensorflow/issues).
 

tensorflow/lite/toco/tflite/export.cc

@@ -16,6 +16,7 @@ limitations under the License.
 
 #include "flatbuffers/flexbuffers.h"
 #include "absl/strings/str_join.h"
+#include "tensorflow/core/lib/core/errors.h"
 #include "tensorflow/lite/context.h"
 #include "tensorflow/lite/schema/schema_generated.h"
 #include "tensorflow/lite/toco/tflite/operator.h"
@@ -431,6 +432,31 @@ tensorflow::Status Export(const Model& model, string* output_file_contents,
   return Export(model, output_file_contents, params, ops_by_type);
 }
 
+void ParseControlFlowErrors(std::set<string>* custom_ops,
+                            std::vector<string>* error_msgs) {
+  std::set<string> unsupported_control_flow_ops;
+  // Check if unsupported ops contains control flow ops. It's impossible
+  // to implement these ops as custom ops at the moment.
+  for (const auto& op : *custom_ops) {
+    if (IsControlFlowOp(op)) {
+      unsupported_control_flow_ops.insert(op);
+    }
+  }
+  if (!unsupported_control_flow_ops.empty()) {
+    error_msgs->push_back(absl::StrCat(
+        "TensorFlow Lite currently doesn't support control flow ops: ",
+        absl::StrJoin(unsupported_control_flow_ops, ", "), ".",
+        " We are working on supporting control flow ops, please see github "
+        "issue at "
+        "https://github.com/tensorflow/tensorflow/issues/28485."));
+  }
+  // Remove control flow ops from `custom_ops` set so that they won't be
+  // reported again in later messages.
+  for (const auto& op : unsupported_control_flow_ops) {
+    custom_ops->erase(op);
+  }
+}
+
 tensorflow::Status Export(
     const Model& model, string* output_file_contents,
     const ExportParams& params,
@@ -483,6 +509,18 @@ tensorflow::Status Export(
 
   if (!custom_ops.empty()) {
     if (!params.allow_custom_ops) {
+      auto please_report_bug_message = []() {
+        return "We are continually in the process of adding support to "
+               "TensorFlow Lite for more ops. It would be helpful if you could "
+               "inform us of how this conversion went by opening a github "
+               "issue at "
+               "https://github.com/tensorflow/tensorflow/issues/new?template="
+               "40-tflite-op-request.md\n and pasting the following:\n\n";
+      };
+
+      std::vector<string> error_msgs;
+      ParseControlFlowErrors(&custom_ops, &error_msgs);
+
       // Remove ExpandDims and ReorderAxes from unimplemented list unless they
       // compose the list. Both ops are removed during graph transformations.
       // However, if an op is unimplemented earlier in the model, the graph
@@ -499,20 +537,12 @@ tensorflow::Status Export(
         custom_ops_final = custom_ops;
       }
 
-      auto please_report_bug_message = []() {
+      if (!custom_ops_final.empty()) {
-        return "We are continually in the process of adding support to "
-               "TensorFlow Lite for more ops. It would be helpful if you could "
-               "inform us of how this conversion went by opening a github "
-               "issue at "
-               "https://github.com/tensorflow/tensorflow/issues/new?template="
-               "40-tflite-op-request.md\n and pasting the following:\n\n";
-      };
-
         if (params.enable_select_tf_ops) {
-        return tensorflow::errors::InvalidArgument(absl::StrCat(
+          error_msgs.push_back(absl::StrCat(
-            please_report_bug_message(),
               "Some of the operators in the model are not supported by "
-            "the standard TensorFlow Lite runtime and are not recognized by "
+              "the standard TensorFlow Lite runtime and are not recognized "
+              "by "
               "TensorFlow. If you have a custom "
               "implementation for them you can disable this error with "
               "--allow_custom_ops, or by setting allow_custom_ops=True "
@@ -523,15 +553,15 @@ tensorflow::Status Export(
               "of operators for which you will need custom implementations: ",
               absl::StrJoin(custom_ops_final, ", "), "."));
         } else {
-        return tensorflow::errors::InvalidArgument(absl::StrCat(
+          error_msgs.push_back(absl::StrCat(
-            please_report_bug_message(),
               "Some of the operators in the model are not supported by "
               "the standard TensorFlow Lite runtime. If those are native "
               "TensorFlow operators, you might be able to use the extended "
               "runtime by passing --enable_select_tf_ops, or by setting "
               "target_ops=TFLITE_BUILTINS,SELECT_TF_OPS when calling "
               "tf.lite.TFLiteConverter(). Otherwise, if you have a "
-            "custom implementation for them you can disable this error with "
+              "custom implementation for them you can disable this error "
+              "with "
               "--allow_custom_ops, or by setting allow_custom_ops=True "
               "when calling tf.lite.TFLiteConverter(). Here is a list "
               "of builtin operators you are using: ",
@@ -541,19 +571,10 @@ tensorflow::Status Export(
               absl::StrJoin(custom_ops_final, ", "), "."));
         }
       }
-
+      if (!error_msgs.empty()) {
-    std::set<string> unsupported_control_flow_ops;
-    // Check if unsupported ops contains control flow ops. It's impossible
-    // to implement these ops as custom ops at the moment.
-    for (const auto& op : custom_ops) {
-      if (IsControlFlowOp(op)) {
-        unsupported_control_flow_ops.insert(op);
-      }
-    }
-    if (!unsupported_control_flow_ops.empty()) {
         return tensorflow::errors::InvalidArgument(absl::StrCat(
-          "TensorFlow Lite currently doesn't support control flow ops: ",
+            please_report_bug_message(), absl::StrJoin(error_msgs, " ")));
-          absl::StrJoin(unsupported_control_flow_ops, ", "), "."));
+      }
     }
   }
 

tensorflow/lite/toco/tflite/export_test.cc

@@ -227,6 +227,123 @@ TEST_F(ExportTest, Export) {
   EXPECT_THAT(ExportAndGetOperatorIndices(params), ElementsAre(1, 0, 2, 3));
 }
 
+TEST_F(ExportTest, UnsupportedControlFlowErrors) {
+  AddOperatorsByName({"Conv", "Add", "Switch", "Merge"});
+
+  ExportParams params;
+  params.allow_custom_ops = false;
+
+  // The model contains control flow ops which are not convertible, so we should
+  // check the returned error message.
+
+  string output;
+  const auto ops_by_type = BuildOperatorByTypeMap();
+  auto status = Export(input_model_, &output, params, ops_by_type);
+  EXPECT_EQ(status.error_message(),
+            "We are continually in the process of adding support to TensorFlow "
+            "Lite for more ops. It would be helpful if you could inform us of "
+            "how this conversion went by opening a github issue at "
+            "https://github.com/tensorflow/tensorflow/issues/"
+            "new?template=40-tflite-op-request.md\n and pasting the "
+            "following:\n\nTensorFlow Lite currently doesn't support control "
+            "flow ops: Merge, Switch. We are working on supporting control "
+            "flow ops, please see github issue at "
+            "https://github.com/tensorflow/tensorflow/issues/28485.");
+}
+
+TEST_F(ExportTest, UnsupportedOpsAndNeedEnableFlex) {
+  AddOperatorsByName({"Conv", "Add", "BatchNormWithGlobalNormalization"});
+
+  ExportParams params;
+  params.allow_custom_ops = false;
+  params.enable_select_tf_ops = false;
+
+  string output;
+  const auto ops_by_type = BuildOperatorByTypeMap();
+  auto status = Export(input_model_, &output, params, ops_by_type);
+  EXPECT_EQ(
+      status.error_message(),
+      "We are continually in the process of adding support to TensorFlow Lite "
+      "for more ops. It would be helpful if you could inform us of how this "
+      "conversion went by opening a github issue at "
+      "https://github.com/tensorflow/tensorflow/issues/"
+      "new?template=40-tflite-op-request.md\n and pasting the "
+      "following:\n\nSome of the operators in the model are not supported by "
+      "the standard TensorFlow Lite runtime. If those are native TensorFlow "
+      "operators, you might be able to use the extended runtime by passing "
+      "--enable_select_tf_ops, or by setting "
+      "target_ops=TFLITE_BUILTINS,SELECT_TF_OPS when calling "
+      "tf.lite.TFLiteConverter(). Otherwise, if you have a custom "
+      "implementation for them you can disable this error with "
+      "--allow_custom_ops, or by setting allow_custom_ops=True when calling "
+      "tf.lite.TFLiteConverter(). Here is a list of builtin operators you are "
+      "using: ADD, CONV_2D. Here is a list of operators for which you will "
+      "need custom implementations: BatchNormWithGlobalNormalization.");
+}
+
+TEST_F(ExportTest, UnsupportedOpsNeedCustomImplementation) {
+  AddOperatorsByName({"Conv", "Add", "MyCustomOp1", "MyCustomOp2"});
+
+  ExportParams params;
+  params.allow_custom_ops = false;
+  params.enable_select_tf_ops = true;
+
+  string output;
+  const auto ops_by_type = BuildOperatorByTypeMap();
+  auto status = Export(input_model_, &output, params, ops_by_type);
+  EXPECT_EQ(
+      status.error_message(),
+      "We are continually in the process of adding support to TensorFlow Lite "
+      "for more ops. It would be helpful if you could inform us of how this "
+      "conversion went by opening a github issue at "
+      "https://github.com/tensorflow/tensorflow/issues/"
+      "new?template=40-tflite-op-request.md\n and pasting the "
+      "following:\n\nSome of the operators in the model are not supported by "
+      "the standard TensorFlow Lite runtime and are not recognized by "
+      "TensorFlow. If you have a custom implementation for them you can "
+      "disable this error with --allow_custom_ops, or by setting "
+      "allow_custom_ops=True when calling tf.lite.TFLiteConverter(). Here is a "
+      "list of builtin operators you are using: ADD, CONV_2D. Here is a list "
+      "of operators for which you will need custom implementations: "
+      "MyCustomOp1, MyCustomOp2.");
+}
+
+TEST_F(ExportTest, UnsupportedControlFlowAndCustomOpsErrors) {
+  AddOperatorsByName(
+      {"Conv", "Add", "Switch", "Merge", "MyCustomOp1", "MyCustomOp2"});
+
+  ExportParams params;
+  params.allow_custom_ops = false;
+
+  // The model contains control flow ops which are not convertible, so we should
+  // check the returned error message.
+
+  string output;
+  const auto ops_by_type = BuildOperatorByTypeMap();
+  auto status = Export(input_model_, &output, params, ops_by_type);
+  EXPECT_EQ(
+      status.error_message(),
+      "We are continually in the process of adding support to TensorFlow Lite "
+      "for more ops. It would be helpful if you could inform us of how this "
+      "conversion went by opening a github issue at "
+      "https://github.com/tensorflow/tensorflow/issues/"
+      "new?template=40-tflite-op-request.md\n and pasting the "
+      "following:\n\nTensorFlow Lite currently doesn't support control flow "
+      "ops: Merge, Switch. We are working on supporting control flow ops, "
+      "please see github issue at "
+      "https://github.com/tensorflow/tensorflow/issues/28485. Some of the "
+      "operators in the model are not supported by the standard TensorFlow "
+      "Lite runtime. If those are native TensorFlow operators, you might be "
+      "able to use the extended runtime by passing --enable_select_tf_ops, or "
+      "by setting target_ops=TFLITE_BUILTINS,SELECT_TF_OPS when calling "
+      "tf.lite.TFLiteConverter(). Otherwise, if you have a custom "
+      "implementation for them you can disable this error with "
+      "--allow_custom_ops, or by setting allow_custom_ops=True when calling "
+      "tf.lite.TFLiteConverter(). Here is a list of builtin operators you are "
+      "using: ADD, CONV_2D. Here is a list of operators for which you will "
+      "need custom implementations: MyCustomOp1, MyCustomOp2.");
+}
+
 TEST_F(ExportTest, QuantizeWeights) {
   // Sanity check for quantize_weights parameter.
   BuildQuantizableTestModel();
@@ -335,7 +452,7 @@ TEST_F(OpSetsTest, BuiltinsAndTfSelect) {
 
 // This test is based on a hypothetical scenario that dilation is supported
 // only in Conv version 2. So Toco populates version=1 when dialation
-// parameters are all 1, and version=2 otehrwise.
+// parameters are all 1, and version=2 otherwise.
 class FakeConvolutionOperator
     : public BuiltinOperator<ConvOperator, ::tflite::Conv2DOptions,
                              ::tflite::BuiltinOptions_Conv2DOptions> {