Automated sync from github.com/tensorflow/tensorflow (#3124)

BUG=automated sync from upstream
NO_CHECK_TFLITE_FILES=automated sync from upstream

Author: TFLM-bot

tensorflow/lite/core/c/common.cc

@@ -104,6 +104,41 @@ void TfLiteVarArrayFree(T* a) {
 
 #ifndef TF_LITE_STATIC_MEMORY
 
+TfLiteSparsity TfLiteSparsityClone(const TfLiteSparsity& src) {
+  TfLiteSparsity dst = src;
+  dst.traversal_order = TfLiteIntArrayCopy(src.traversal_order);
+  dst.block_map = TfLiteIntArrayCopy(src.block_map);
+  if (src.dim_metadata) {
+    dst.dim_metadata = reinterpret_cast<TfLiteDimensionMetadata*>(
+        calloc(1, sizeof(TfLiteDimensionMetadata) * src.dim_metadata_size));
+    for (int i = 0; i < src.dim_metadata_size; ++i) {
+      dst.dim_metadata[i] = src.dim_metadata[i];
+      dst.dim_metadata[i].array_segments =
+          TfLiteIntArrayCopy(src.dim_metadata[i].array_segments);
+      dst.dim_metadata[i].array_indices =
+          TfLiteIntArrayCopy(src.dim_metadata[i].array_indices);
+    }
+  }
+  return dst;
+}
+
+// Clones the source sparsity to a newly allocated object.
+TfLiteSparsity* TfLiteSparsityClone(const TfLiteSparsity* const src) {
+  if (!src) {
+    return nullptr;
+  }
+  TfLiteSparsity* dst =
+      reinterpret_cast<TfLiteSparsity*>(calloc(1, sizeof(TfLiteSparsity)));
+  *dst = TfLiteSparsityClone(*src);
+  return dst;
+}
+
+#endif  // TF_LITE_STATIC_MEMORY
+
+}  // namespace
+
+#ifndef TF_LITE_STATIC_MEMORY
+
 TfLiteQuantization TfLiteQuantizationClone(const TfLiteQuantization& src) {
   TfLiteQuantization dst;
   dst.type = src.type;
@@ -136,39 +171,8 @@ TfLiteQuantization TfLiteQuantizationClone(const TfLiteQuantization& src) {
   return dst;
 }
 
-TfLiteSparsity TfLiteSparsityClone(const TfLiteSparsity& src) {
-  TfLiteSparsity dst = src;
-  dst.traversal_order = TfLiteIntArrayCopy(src.traversal_order);
-  dst.block_map = TfLiteIntArrayCopy(src.block_map);
-  if (src.dim_metadata) {
-    dst.dim_metadata = reinterpret_cast<TfLiteDimensionMetadata*>(
-        calloc(1, sizeof(TfLiteDimensionMetadata) * src.dim_metadata_size));
-    for (int i = 0; i < src.dim_metadata_size; ++i) {
-      dst.dim_metadata[i] = src.dim_metadata[i];
-      dst.dim_metadata[i].array_segments =
-          TfLiteIntArrayCopy(src.dim_metadata[i].array_segments);
-      dst.dim_metadata[i].array_indices =
-          TfLiteIntArrayCopy(src.dim_metadata[i].array_indices);
-    }
-  }
-  return dst;
-}
-
-// Clones the source sparsity to a newly allocated object.
-TfLiteSparsity* TfLiteSparsityClone(const TfLiteSparsity* const src) {
-  if (!src) {
-    return nullptr;
-  }
-  TfLiteSparsity* dst =
-      reinterpret_cast<TfLiteSparsity*>(calloc(1, sizeof(TfLiteSparsity)));
-  *dst = TfLiteSparsityClone(*src);
-  return dst;
-}
-
 #endif  // TF_LITE_STATIC_MEMORY
 
-}  // namespace
-
 extern "C" {
 
 size_t TfLiteIntArrayGetSizeInBytes(int size) {
@@ -247,6 +251,11 @@ void TfLiteQuantizationFree(TfLiteQuantization* quantization) {
     }
     free(q_params);
   }
+  if (quantization->type == kTfLiteBlockwiseQuantization) {
+    TfLiteBlockwiseQuantization* q_params =
+        reinterpret_cast<TfLiteBlockwiseQuantization*>(quantization->params);
+    free(q_params);
+  }
   quantization->params = nullptr;
   quantization->type = kTfLiteNoQuantization;
 }

tensorflow/lite/core/c/common.h

@@ -788,6 +788,7 @@ TfLiteStatus TfLiteTensorRealloc(size_t num_bytes, TfLiteTensor* tensor);
 /// If all dimensions are known, this is the same as `t->dims`.
 /// (`dims_signature` is NULL or empty if all dimensions are known.)
 const TfLiteIntArray* TfLiteTensorGetDimsSignature(const TfLiteTensor* t);
+
 #endif  // TF_LITE_STATIC_MEMORY
 
 /// WARNING: This is an experimental interface that is subject to change.
@@ -1633,5 +1634,8 @@ TfLiteStatus TfLiteTensorVariantRealloc(TfLiteTensor* t,
   return kTfLiteOk;
 }
 
+// Returns a copy of the quantization parameters of the tensor.
+TfLiteQuantization TfLiteQuantizationClone(const TfLiteQuantization& src);
+
 #endif  // __cplusplus
 #endif  // TENSORFLOW_LITE_CORE_C_COMMON_H_

tensorflow/lite/tools/visualize.py

@@ -43,6 +43,16 @@
 body {font-family: sans-serif; background-color: #fa0;}
 table {background-color: #eca;}
 th {background-color: black; color: white;}
+/* Constrain table cells to a max size and make them scrollable. */
+.data-table td {
+  max-width: 900px;
+}
+.data-table .cell-content {
+  max-height: 200px;
+  overflow: auto;
+  white-space: pre-wrap;
+  word-break: break-all;
+}
 h1 {
   background-color: ffaa00;
   padding:5px;
@@ -284,6 +294,27 @@ def __call__(self, x):
     return html
 
 
+def QuantizationMapper(q):
+  """Pretty-print the quantization dictionary, truncating large arrays."""
+  if not q:
+    return ""
+
+  items_str = []
+  for key, value in q.items():
+    key_str = repr(key)
+    # In TFLite, quantization arrays can be large.
+    if isinstance(value, list) and len(value) > 20:
+      head = value[:10]
+      tail = value[-10:]
+      value_str = (f"[{', '.join(map(repr, head))}, ..., "
+                   f"{', '.join(map(repr, tail))}]")
+    else:
+      value_str = repr(value)
+    items_str.append(f"{key_str}: {value_str}")
+
+  return f"{{{', '.join(items_str)}}}"
+
+
 def GenerateGraph(subgraph_idx, g, opcode_mapper):
   """Produces the HTML required to have a d3 visualization of the dag."""
 
@@ -359,8 +390,8 @@ def GenerateTableHtml(items, keys_to_print, display_index=True):
     An html table.
   """
   html = ""
-  # Print the list of  items
-  html += "<table><tr>\n"
+  # Print the list of items
+  html += "<table class='data-table'>\n"
   html += "<tr>\n"
   if display_index:
     html += "<th>index</th>"
@@ -375,7 +406,7 @@ def GenerateTableHtml(items, keys_to_print, display_index=True):
     for h, mapper in keys_to_print:
       val = tensor[h] if h in tensor else None
       val = val if mapper is None else mapper(val)
-      html += "<td>%s</td>\n" % val
+      html += "<td><div class='cell-content'>%s</div></td>\n" % val
 
     html += "</tr>\n"
   html += "</table>\n"
@@ -465,11 +496,13 @@ def create_html(tflite_input, input_is_filepath=True):  # pylint: disable=invali
   toplevel_stuff = [("filename", None), ("version", None),
                     ("description", None)]
 
-  html += "<table>\n"
+  html += "<table class='data-table'>\n"
   for key, mapping in toplevel_stuff:
     if not mapping:
       mapping = lambda x: x
-    html += "<tr><th>%s</th><td>%s</td></tr>\n" % (key, mapping(data.get(key)))
+    val = mapping(data.get(key))
+    html += ("<tr><th>%s</th><td><div class='cell-content'>%s</div></td></tr>\n"
+             % (key, val))
   html += "</table>\n"
 
   # Spec on what keys to display
@@ -493,7 +526,7 @@ def create_html(tflite_input, input_is_filepath=True):  # pylint: disable=invali
     tensor_keys_to_display = [("name", NameListToString),
                               ("type", TensorTypeToName), ("shape", None),
                               ("shape_signature", None), ("buffer", None),
-                              ("quantization", None)]
+                              ("quantization", QuantizationMapper)]
 
     html += "<h2>Subgraph %d</h2>\n" % subgraph_idx