Fix bazel TFLM compilation w/ TF_LITE_STATIC_MEMORY

Ensure dynamic string utils aren't compiled when this build define is
present.

PiperOrigin-RevId: 311626904
Change-Id: Ica229bf337019f0f446fdb94aaf42c6b7e7c749e

tensorflow/lite/kernels/BUILD

@@ -386,7 +386,7 @@ cc_library(
         "//tensorflow/lite/c:common",
         "//tensorflow/lite/kernels/internal:cppmath",
         "//tensorflow/lite/kernels/internal:quantization_util",
-        "@flatbuffers",
+        "@flatbuffers//:runtime_cc",
     ],
 )
 

tensorflow/lite/kernels/internal/BUILD

@@ -629,7 +629,6 @@ cc_library(
         ":cppmath",
         "//tensorflow/lite:minimal_logging",
         "//tensorflow/lite/c:common",
-        "//tensorflow/lite/kernels:cpu_backend_context",
         "@gemmlowp",
     ],
 )
@@ -785,7 +784,6 @@ cc_library(
     deps = [
         ":cpu_check",
         "//tensorflow/lite/c:common",
-        "//tensorflow/lite/kernels:cpu_backend_context",
         "//third_party/eigen3",
     ],
 )
@@ -819,6 +817,7 @@ cc_test(
         ":quantization_util",
         ":tensor_utils",
         "//tensorflow/lite/c:common",
+        "//tensorflow/lite/kernels:cpu_backend_context",
         "//tensorflow/lite/kernels:test_util",
         "@com_google_googletest//:gtest_main",
     ],

tensorflow/lite/kernels/internal/reference/portable_tensor_utils.cc

@@ -21,7 +21,6 @@ limitations under the License.
 
 #include "fixedpoint/fixedpoint.h"
 #include "tensorflow/lite/c/builtin_op_data.h"
-#include "tensorflow/lite/kernels/cpu_backend_context.h"
 #include "tensorflow/lite/kernels/internal/common.h"
 #include "tensorflow/lite/kernels/internal/compatibility.h"
 #include "tensorflow/lite/kernels/internal/cppmath.h"
@@ -53,7 +52,7 @@ void PortableSymmetricQuantizeFloats(const float* values, const int size,
 void PortableSymmetricQuantizeFloats(const float* values, const int size,
                                      int8_t* quantized_values, float min_value,
                                      float max_value, float* scaling_factor) {
-  const int kScale = 127;
+  const int32_t kScale = 127;
   const float range = std::max(std::abs(min_value), std::abs(max_value));
   if (range == 0) {
     memset(quantized_values, 0, size * sizeof(int8_t));
@@ -66,7 +65,8 @@ void PortableSymmetricQuantizeFloats(const float* values, const int size,
     const int32_t quantized_value =
         static_cast<int32_t>(TfLiteRound(values[i] * scaling_factor_inv));
     // Clamp: just in case some odd numeric offset.
-    quantized_values[i] = std::min(kScale, std::max(-kScale, quantized_value));
+    quantized_values[i] = static_cast<int8_t>(
+        std::min(kScale, std::max(-kScale, quantized_value)));
   }
 }
 
@@ -660,7 +660,8 @@ void PortableCwiseMul(const int16_t* input_1, const int16_t* input_2,
       int32_t value = static_cast<int32_t>(a) * static_cast<int32_t>(b);
       value = MultiplyByQuantizedMultiplier(value, multiplier, shift);
       value -= output_zp;
-      value = std::min(std::max(-128, value), 127);
+      value = std::min(std::max(static_cast<int32_t>(-128), value),
+                       static_cast<int32_t>(127));
 
       output[index] = static_cast<int8>(value);
     }
@@ -748,7 +749,8 @@ void PortableVectorBatchVectorCwiseProductAccumulate(
       int32_t prod = vector[v] * *batch_vector++;
       prod = MultiplyByQuantizedMultiplier(prod, multiplier, shift);
       int32_t output = prod + *result;
-      output = std::max(std::min(32767, output), -32768);
+      output = std::max(std::min(static_cast<int32_t>(32767), output),
+                        static_cast<int32_t>(-32768));
       *result++ = output;
     }
   }

tensorflow/lite/kernels/internal/reference/portable_tensor_utils.h

@@ -18,7 +18,6 @@ limitations under the License.
 // TODO(ghodrat): Remove this header file and the dependency to internal data
 // structure.
 #include "tensorflow/lite/c/builtin_op_data.h"
-#include "tensorflow/lite/kernels/cpu_backend_context.h"
 #include "tensorflow/lite/kernels/internal/reference/portable_tensor_utils_impl.h"
 
 #if defined(_MSC_VER)

tensorflow/lite/kernels/internal/reference/portable_tensor_utils_impl.h

@@ -20,13 +20,17 @@ limitations under the License.
 // TODO(ghodrat): Remove this header file and the dependency to internal data
 // structure.
 #include "tensorflow/lite/c/builtin_op_data.h"
-#include "tensorflow/lite/kernels/cpu_backend_context.h"
 
 #if defined(_MSC_VER)
 #define __restrict__ __restrict
 #endif
 
 namespace tflite {
+
+// Not all backends support CpuBackendContext usage, so forward declare to avoid
+// pulling in its implementation.
+class CpuBackendContext;
+
 namespace tensor_utils {
 
 // Limit a float input f between +abs_limit and -abs_limit.

tensorflow/lite/kernels/internal/tensor.h

@@ -119,6 +119,8 @@ class SequentialTensorWriter {
   T* output_ptr_;
 };
 
+// String ops are not yet supported on platforms w/ static memory.
+#ifndef TF_LITE_STATIC_MEMORY
 template <>
 class SequentialTensorWriter<string> {
  public:
@@ -138,6 +140,7 @@ class SequentialTensorWriter<string> {
   TfLiteTensor* output_;
   DynamicBuffer buffer_;
 };
+#endif  // TF_LITE_STATIC_MEMORY
 
 }  // namespace tflite
 

tensorflow/lite/kernels/internal/tensor_utils.h

@@ -20,13 +20,18 @@ limitations under the License.
 
 #include "third_party/eigen3/Eigen/Core"
 #include "tensorflow/lite/c/builtin_op_data.h"
-#include "tensorflow/lite/kernels/cpu_backend_context.h"
 
 #if defined(_MSC_VER)
 #define __restrict__ __restrict
 #endif
 
 namespace tflite {
+
+// Not all backends support CpuBackendContext usage, so forward declare to avoid
+// pulling in its implementation. Use of CpuBackendContext in method
+// implementations is purely optional.
+class CpuBackendContext;
+
 namespace tensor_utils {
 
 // Checks if all entries of vector are zero for float.

tensorflow/lite/kernels/internal/tensor_utils_test.cc

@@ -18,6 +18,7 @@ limitations under the License.
 
 #include <gmock/gmock.h>
 #include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/kernels/cpu_backend_context.h"
 #include "tensorflow/lite/kernels/internal/common.h"
 #include "tensorflow/lite/kernels/internal/quantization_util.h"
 #include "tensorflow/lite/kernels/test_util.h"

tensorflow/lite/kernels/non_max_suppression.cc

@@ -19,7 +19,6 @@ limitations under the License.
 #include <numeric>
 #include <vector>
 
-#include "flatbuffers/flexbuffers.h"  // from @flatbuffers
 #include "tensorflow/lite/c/builtin_op_data.h"
 #include "tensorflow/lite/c/common.h"
 #include "tensorflow/lite/kernels/internal/tensor.h"

tensorflow/lite/string_util.cc

@@ -89,6 +89,7 @@ int DynamicBuffer::WriteToBuffer(char** buffer) {
   return bytes;
 }
 
+#ifndef TF_LITE_STATIC_MEMORY
 void DynamicBuffer::WriteToTensorAsVector(TfLiteTensor* tensor) {
   auto dims = TfLiteIntArrayCreate(1);
   dims->data[0] = offset_.size() - 1;  // Store number of strings.
@@ -109,6 +110,7 @@ void DynamicBuffer::WriteToTensor(TfLiteTensor* tensor,
                     tensor_buffer, bytes, kTfLiteDynamic, tensor->allocation,
                     tensor->is_variable, tensor);
 }
+#endif  // TF_LITE_STATIC_MEMORY
 
 int GetStringCount(const void* raw_buffer) {
   // The first integers in the raw buffer is the number of strings.

tensorflow/lite/string_util.h

@@ -74,6 +74,9 @@ class DynamicBuffer {
   // The function allocates space for the buffer but does NOT take ownership.
   int WriteToBuffer(char** buffer);
 
+  // String tensors are not generally supported on platforms w/ static memory.
+  // TODO(b/156130024): Remove this guard after removing header from TFLM deps.
+#ifndef TF_LITE_STATIC_MEMORY
   // Fill content into a string tensor, with the given new_shape. The new shape
   // must match the number of strings in this object. Caller relinquishes
   // ownership of new_shape. If 'new_shape' is nullptr, keep the tensor's
@@ -82,6 +85,7 @@ class DynamicBuffer {
 
   // Fill content into a string tensor. Set shape to {num_strings}.
   void WriteToTensorAsVector(TfLiteTensor* tensor);
+#endif  // TF_LITE_STATIC_MEMORY
 
  private:
   // Data buffer to store contents of strings, not including headers.