Update generate_cc_arrays to take any filetype

- If the filetype isn't a special one that the script knows, simply
  process the data into an array of bytes instead of giving up.

Change-Id: I531d8cd8f9f1692570d0cf51e6eace2f83ef2e92

tensorflow/lite/micro/tools/generate_cc_arrays.py

diff --git a/tensorflow/lite/micro/tools/generate_cc_arrays.py b/tensorflow/lite/micro/tools/generate_cc_arrays.py
index 4d1e54c..759db56 100644
--- a/tensorflow/lite/micro/tools/generate_cc_arrays.py
+++ b/tensorflow/lite/micro/tools/generate_cc_arrays.py
@@ -94,9 +94,12 @@
     data_1d = data.flatten()
     out_string = ','.join([str(x) for x in data_1d])
     return [len(data_1d), out_string]
-
   else:
-    raise ValueError('input file must be .tflite, .bmp, .wav or .csv')
+    with open(input_fname, 'rb') as input_file:
+      buffer = input_file.read()
+    size = len(buffer)
+    out_string = bytes_to_hexstring(buffer)
+    return [size, out_string]
 
 
 def get_array_name(input_fname):
@@ -119,6 +122,8 @@
     return [base_array_name + '_test_data', 'float']
   elif input_fname.endswith('npy'):
     return [base_array_name + '_test_data', 'float']
+  else:
+    return [base_array_name, 'unsigned char']
 
 
 def main():