feat(compression): enhance view.py to display decoded LUT indices

Add functionality to decode and display LUT indices for compressed
tensor buffers in the model viewer. When viewing compressed models,
buffers containing compressed data now show a "_lut_indices" field
with the decoded indices displayed in a readable multi-line format.

Also improve the numpy array pretty printer to display all values
without ellipsis truncation, making large arrays more readable.

Author: rkuester

tensorflow/lite/micro/compression/view.py

@@ -350,6 +350,28 @@ def unpack_compression_metadata(buffer):
   return {"subgraphs": result}
 
 
+def find_lut_info_for_buffer(buffer_index, model, compression_data):
+  """Find LUT metadata for a given buffer index.
+  
+  Returns a dict with tensor_index, subgraph_index, and index_bitwidth if the
+  buffer contains compressed indices, otherwise returns None.
+  """
+  if compression_data is None:
+    return None
+    
+  for subgraph_idx, subgraph in enumerate(compression_data.metadata.subgraphs):
+    for lut_tensor in subgraph.lutTensors:
+      # Get the tensor to find which buffer contains the compressed indices
+      tensor = model.subgraphs[subgraph_idx].tensors[lut_tensor.tensor]
+      if tensor.buffer == buffer_index:
+        return {
+            "tensor_index": lut_tensor.tensor,
+            "subgraph_index": subgraph_idx,
+            "index_bitwidth": lut_tensor.indexBitwidth,
+        }
+  return None
+
+
 def unpack_buffers(model, compression_data):
   buffers = []
   for index, buffer in enumerate(model.buffers):
@@ -362,6 +384,25 @@ def unpack_buffers(model, compression_data):
       native["_compression_metadata"] = True
 
     native["data"] = buffer.data
+    
+    # Check if this buffer contains compressed indices
+    lut_info = find_lut_info_for_buffer(index, model, compression_data)
+    if lut_info and buffer.data is not None:
+      # Decode the indices from the buffer
+      bstring = bitarray.bitarray()
+      bstring.frombytes(bytes(buffer.data))
+      bitwidth = lut_info["index_bitwidth"]
+      chunks = [bstring[i:i+bitwidth] for i in range(0, len(bstring) - bitwidth + 1, bitwidth)]
+      indices = [bitarray.util.ba2int(chunk) for chunk in chunks]
+      
+      # Convert indices to numpy array to match data field formatting
+      indices_array = np.array(indices, dtype=np.uint8)
+      
+      native["_lut_indices"] = {
+          "tensor": lut_info["tensor_index"],
+          "bitwidth": bitwidth,
+          "indices": indices_array,
+      }
 
     buffers.append(native)
 
@@ -404,7 +445,9 @@ def create_dictionary(flatbuffer: memoryview) -> dict:
 
 @prettyprinter.register_pretty(np.ndarray)
 def pretty_numpy_array(array, ctx):
-  string = np.array2string(array)
+  # Format array without ellipsis, similar to how buffer data is displayed
+  string = np.array2string(array, threshold=np.inf, max_line_width=78, 
+                           separator=' ', suppress_small=True)
   lines = string.splitlines()
 
   if len(lines) == 1: