Sync from upstream TF.

Author: TFLM-bot

tensorflow/lite/core/c/common.h

@@ -1060,6 +1060,13 @@ typedef struct TfLiteContext {
   /// WARNING: This is an experimental interface that is subject to change.
   TfLiteStatus (*ReleaseSubgraphContext)(struct TfLiteContext* context,
                                          int subgraph_index);
+#if defined(_WIN32)
+  /// Create a array of a given `size` (uninitialized entries).
+  TfLiteIntArray* (*TfLiteIntArrayCreate)(int size);  // NOLINT
+
+  /// Free memory of array `a`.
+  void (*TfLiteIntArrayFree)(TfLiteIntArray* a);  // NOLINT
+#endif                                            // defined(_WIN32)
 } TfLiteContext;
 
 /// `TfLiteOperator` is an external version of `TfLiteRegistration`

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

@@ -17,6 +17,7 @@ limitations under the License.
 #define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_CONCATENATION_H_
 
 #include <algorithm>
+#include <cstddef>
 
 #include "tensorflow/lite/kernels/internal/common.h"
 #include "tensorflow/lite/kernels/internal/compatibility.h"
@@ -109,7 +110,7 @@ inline void Concatenation<Int4>(const ConcatenationParams& params,
   // not garbage.
   // Note: output_shape.FlatSize() gives number of elements (nibbles).
   // Bytes needed: (elements + 1) / 2.
-  memset(output_ptr, 0, (output_shape.FlatSize() + 1) / 2);
+  memset(output_ptr, 0, (static_cast<size_t>(output_shape.FlatSize()) + 1) / 2);
 
   int64_t output_offset = 0;
   for (int k = 0; k < outer_size; k++) {

tensorflow/lite/kernels/kernel_util.cc

@@ -25,6 +25,7 @@ limitations under the License.
 #ifndef TF_LITE_STATIC_MEMORY
 #include <string>
 
+#include "absl/types/span.h"
 #include "tensorflow/lite/array.h"
 #endif  // TF_LITE_STATIC_MEMORY
 
@@ -33,6 +34,7 @@ limitations under the License.
 #include "tensorflow/lite/core/c/common.h"
 #include "tensorflow/lite/kernels/internal/cppmath.h"
 #include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/util.h"
 
 #if defined(__APPLE__)
 #include "TargetConditionals.h"
@@ -595,4 +597,25 @@ bool HasUnspecifiedDimension(const TfLiteTensor* tensor) {
   return false;
 }
 
+TfLiteStatus CheckedShapeProduct(TfLiteContext* context,
+                                 absl::Span<const int> dims,
+                                 const char* error_message, size_t& product) {
+  // The CheckedNumElements function already checks for negative dimensions, so
+  // we don't do it here.
+  TF_LITE_ENSURE_MSG(context, CheckedNumElements(dims, product) == kTfLiteOk,
+                     "%s", error_message);
+  return kTfLiteOk;
+}
+
+TfLiteStatus CheckedShapeProductToInt(TfLiteContext* context,
+                                      absl::Span<const int> dims,
+                                      const char* error_message, int& product) {
+  for (const int dim : dims) {
+    TF_LITE_ENSURE_MSG(context, dim >= 0, "Encountered a negative dimension.");
+  }
+  TF_LITE_ENSURE_MSG(context, CheckedNumElements(dims, product) == kTfLiteOk,
+                     "%s", error_message);
+  return kTfLiteOk;
+}
+
 }  // namespace tflite

tensorflow/lite/kernels/kernel_util.h

@@ -17,11 +17,13 @@ limitations under the License.
 
 #include <stdint.h>
 
+#include <cstddef>
 #include <limits>
 #ifndef TF_LITE_STATIC_MEMORY
 #include <string>
 #endif  // TF_LITE_STATIC_MEMORY
 
+#include "absl/types/span.h"
 #include "tensorflow/lite/core/c/builtin_op_data.h"
 #include "tensorflow/lite/core/c/common.h"
 #ifndef NDEBUG
@@ -341,6 +343,30 @@ bool IsMobilePlatform();
 // Returns whether there is unspecified dimension in the tensor's dim signature.
 bool HasUnspecifiedDimension(const TfLiteTensor* tensor);
 
+/**
+ * Calculates the product of the given dimensions. Returns an error if any of
+ * the dimensions is negative or if the product overflows.
+ * @param context The context to use for error reporting.
+ * @param dims The dimensions to multiply.
+ * @param error_message The error message to use if an error is encountered.
+ * @param product The output parameter to store the product.
+ */
+TfLiteStatus CheckedShapeProduct(TfLiteContext* context,
+                                 absl::Span<const int> dims,
+                                 const char* error_message, size_t& product);
+
+/**
+ * Calculates the product of the given dimensions. Returns an error if any of
+ * the dimensions is negative or if the product overflows.
+ * @param context The context to use for error reporting.
+ * @param dims The dimensions to multiply.
+ * @param error_message The error message to use if an error is encountered.
+ * @param product The output parameter to store the product.
+ */
+TfLiteStatus CheckedShapeProductToInt(TfLiteContext* context,
+                                      absl::Span<const int> dims,
+                                      const char* error_message, int& product);
+
 }  // namespace tflite
 
 #endif  // TENSORFLOW_LITE_KERNELS_KERNEL_UTIL_H_

tensorflow/lite/tools/flatbuffer_utils_test.py

@@ -18,9 +18,9 @@
 import subprocess
 import sys
 
-from tflite_micro.tensorflow.lite.python import schema_py_generated as schema  # pylint:disable=g-direct-tensorflow-import
-from tflite_micro.tensorflow.lite.tools import flatbuffer_utils
-from tflite_micro.tensorflow.lite.tools import test_utils
+from tflite_micro.tensorflow.lite_micro.tensorflow.lite.python import schema_py_generated as schema  # pylint:disable=g-direct-tensorflow-import
+from tflite_micro.tensorflow.lite_micro.tensorflow.lite.tools import flatbuffer_utils
+from tflite_micro.tensorflow.lite_micro.tensorflow.lite.tools import test_utils
 from tensorflow.python.framework import test_util
 from tensorflow.python.platform import test
 

tensorflow/lite/tools/test_utils.py

@@ -18,7 +18,7 @@
 """
 
 import flatbuffers
-from tflite_micro.tensorflow.lite.python import schema_py_generated as schema_fb
+from tflite_micro.tensorflow.lite_micro.tensorflow.lite.python import schema_py_generated as schema_fb
 
 TFLITE_SCHEMA_VERSION = 3
 

tensorflow/lite/tools/visualize_test.py

@@ -16,8 +16,8 @@
 import os
 import re
 
-from tflite_micro.tensorflow.lite.tools import test_utils
-from tflite_micro.tensorflow.lite.tools import visualize
+from tflite_micro.tensorflow.lite_micro.tensorflow.lite.tools import test_utils
+from tflite_micro.tensorflow.lite_micro.tensorflow.lite.tools import visualize
 from tensorflow.python.framework import test_util
 from tensorflow.python.platform import test