| Index: src/trusted/validator_arm/dgen_opt.py
|
| diff --git a/src/trusted/validator_arm/dgen_opt.py b/src/trusted/validator_arm/dgen_opt.py
|
| deleted file mode 100644
|
| index 806333c2ab8fa11516368adaa0a89301cd767749..0000000000000000000000000000000000000000
|
| --- a/src/trusted/validator_arm/dgen_opt.py
|
| +++ /dev/null
|
| @@ -1,76 +0,0 @@
|
| -#!/usr/bin/python
|
| -#
|
| -# Copyright 2009 The Native Client Authors. All rights reserved.
|
| -# Use of this source code is governed by a BSD-style license that can
|
| -# be found in the LICENSE file.
|
| -# Copyright 2009, Google Inc.
|
| -#
|
| -
|
| -"""
|
| -Table minimization algorithm.
|
| -"""
|
| -
|
| -def optimize_rows(rows):
|
| - """Breaks rows up into batches, and attempts to minimize each batch,
|
| - using _optimize_rows_for_single_action.
|
| - """
|
| - rows_by_action = dict()
|
| - for row in rows:
|
| - if (row.action, row.arch) in rows_by_action:
|
| - rows_by_action[(row.action, row.arch)].append(row)
|
| - else:
|
| - rows_by_action[(row.action, row.arch)] = [row]
|
| -
|
| - optimized_rows = []
|
| - for row_group in rows_by_action.itervalues():
|
| - optimized_rows.extend(_optimize_rows_for_single_action(row_group))
|
| -
|
| - _remove_unused_columns(optimized_rows)
|
| - return optimized_rows
|
| -
|
| -def _optimize_rows_for_single_action(rows):
|
| - """Performs basic automatic minimization on the given rows.
|
| -
|
| - Repeatedly selects a pair of rows to merge. Recurses until no suitable pair
|
| - can be found. It's not real smart, and is O(n^2).
|
| -
|
| - A pair of rows is compatible if all columns are equal, or if exactly one
|
| - row differs but is_strictly_compatible.
|
| - """
|
| - for (i, j) in each_index_pair(rows):
|
| - row_i, row_j = rows[i], rows[j]
|
| -
|
| - if row_i.can_merge(row_j):
|
| - new_rows = list(rows)
|
| - del new_rows[j]
|
| - del new_rows[i]
|
| - new_rows.append(row_i + row_j)
|
| - return _optimize_rows_for_single_action(new_rows)
|
| -
|
| - # No changes made:
|
| - return rows
|
| -
|
| -def _remove_unused_columns(rows):
|
| - num_cols = len(rows[0].patterns)
|
| - used = [False] * num_cols
|
| -
|
| - for r in rows:
|
| - for i in range(0, num_cols):
|
| - if r.patterns[i].mask != 0:
|
| - used[i] = True
|
| -
|
| - if not True in used:
|
| - # Always preserve at least one column
|
| - used[0] = True
|
| -
|
| - for col in range(num_cols - 1, 0 - 1, -1):
|
| - for r in rows:
|
| - if not used[col]:
|
| - del r.patterns[col]
|
| -
|
| -
|
| -def each_index_pair(sequence):
|
| - """Utility function: Generates each unique index pair in sequence."""
|
| - for i in range(0, len(sequence)):
|
| - for j in range(i + 1, len(sequence)):
|
| - yield (i, j)
|
|
|