テンソルフローのブロードキャストでは何がサポートされていますか？寸法がどのように一致するか？

Question

githubで問題を提起しました：https://github.com/tensorflow/tensorflow/issues/14924ここに詳細があります。

これはOKです：

import tensorflow as tf 
sess = tf.InteractiveSession() 
xx = tf.constant(1, shape=[32,1,4,4,1], dtype=tf.float32) 
yy = tf.constant(1, shape=[1,32,1,4,4], dtype=tf.float32) 
zz = xx * yy 
sess.run([zz]) 

しかし：

UnimplementedError (see above for traceback): Broadcast between [10,32,1,4,4,1] and [10,1,32,1,4,4] is not supported yet. [[Node: mul_1 = Mul[T=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](Const_2, Const_3)]] 

ログイン：

--------------------------------------------------------------------------- 
UnimplementedError      Traceback (most recent call last) 
<ipython-input-2-eef82717f8d8> in <module>() 
     2 y2 = tf.constant(1, shape=[10,1,32,1,4,4]) 
     3 z2 = x2 * y2 
----> 4 sess.run(z2) 

/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in run(self, fetches, feed_dict, options, run_metadata) 
    887  try: 
    888  result = self._run(None, fetches, feed_dict, options_ptr, 
--> 889       run_metadata_ptr) 
    890  if run_metadata: 
    891   proto_data = tf_session.TF_GetBuffer(run_metadata_ptr) 

/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _run(self, handle, fetches, feed_dict, options, run_metadata) 
    1118  if final_fetches or final_targets or (handle and feed_dict_tensor): 
    1119  results = self._do_run(handle, final_targets, final_fetches, 
-> 1120        feed_dict_tensor, options, run_metadata) 
    1121  else: 
    1122  results = [] 

/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata) 
    1315  if handle is None: 
    1316  return self._do_call(_run_fn, self._session, feeds, fetches, targets, 
-> 1317       options, run_metadata) 
    1318  else: 
    1319  return self._do_call(_prun_fn, self._session, handle, feeds, fetches) 

/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _do_call(self, fn, *args) 
    1334   except KeyError: 
    1335   pass 
-> 1336  raise type(e)(node_def, op, message) 
    1337 
    1338 def _extend_graph(self): 

UnimplementedError: Broadcast between [10,32,1,4,4,1] and [10,1,32,1,4,4] is not supported yet. 
    [[Node: mul_1 = Mul[T=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](Const_2, Const_3)]] 

Caused by op u'mul_1', defined at: 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/runpy.py", line 174, in _run_module_as_main 
    "__main__", fname, loader, pkg_name) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/runpy.py", line 72, in _run_code 
    exec code in run_globals 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/ipykernel/__main__.py", line 3, in <module> 
    app.launch_new_instance() 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/traitlets/config/application.py", line 658, in launch_instance 
    app.start() 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/ipykernel/kernelapp.py", line 474, in start 
    ioloop.IOLoop.instance().start() 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/zmq/eventloop/ioloop.py", line 177, in start 
    super(ZMQIOLoop, self).start() 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/tornado/ioloop.py", line 887, in start 
    handler_func(fd_obj, events) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/tornado/stack_context.py", line 275, in null_wrapper 
    return fn(*args, **kwargs) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events 
    self._handle_recv() 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv 
    self._run_callback(callback, msg) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback 
    callback(*args, **kwargs) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/tornado/stack_context.py", line 275, in null_wrapper 
    return fn(*args, **kwargs) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 276, in dispatcher 
    return self.dispatch_shell(stream, msg) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell 
    handler(stream, idents, msg) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 390, in execute_request 
    user_expressions, allow_stdin) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/ipykernel/ipkernel.py", line 196, in do_execute 
    res = shell.run_cell(code, store_history=store_history, silent=silent) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/ipykernel/zmqshell.py", line 501, in run_cell 
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2717, in run_cell 
    interactivity=interactivity, compiler=compiler, result=result) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes 
    if self.run_code(code, result): 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2881, in run_code 
    exec(code_obj, self.user_global_ns, self.user_ns) 
    File "<ipython-input-2-eef82717f8d8>", line 3, in <module> 
    z2 = x2 * y2 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/tensorflow/python/ops/math_ops.py", line 894, in binary_op_wrapper 
    return func(x, y, name=name) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/tensorflow/python/ops/math_ops.py", line 1117, in _mul_dispatch 
    return gen_math_ops._mul(x, y, name=name) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/tensorflow/python/ops/gen_math_ops.py", line 2726, in _mul 
    "Mul", x=x, y=y, name=name) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper 
    op_def=op_def) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2956, in create_op 
    op_def=op_def) 
    File "/home/jetadmin/anaconda2/envs/ygtf/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1470, in __init__ 
    self._traceback = self._graph._extract_stack() # pylint: disable=protected-access 

UnimplementedError (see above for traceback): Broadcast between [10,32,1,4,4,1] and [10,1,32,1,4,4] is not supported yet. 
    [[Node: mul_1 = Mul[T=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](Const_2, Const_3)]] 

x2 = tf.constant(1, shape=[10,32,1,4,4,1]) 
y2 = tf.constant(1, shape=[10,1,32,1,4,4]) 
z2 = x2 * y2 
sess.run(z2) 

はエラーになります更新：

理由の合計が次元の総数または不一致の数ではなく、一致する方法に関係していると考えます。次のスクリプトは正常に実行されるため、x3は2から最後の次元が4から1に変更され、不一致箇所が1つ増えます。

x3 = tf.constant(1, shape=[10,32,1,4,1,1]) 
y3 = tf.constant(1, shape=[10,1,32,1,4,4]) 
z3 = x3 * y3 
sess.run(z3) 

Answer 1

Tensorflowは、すでに遵守しているように、ブロードキャストするために修正する次元の不一致の数を制限しています。

この目的のために、さまざまな数のテンソルを1つの共通の形にブロードキャストする私自身の放送機能を作成しました。ただし、テンソルの形状が定義されていないか、形状がNoneの場合、この関数は機能しません。

def broadcast_tensors(tensors): 
    shapes = [t.get_shape().as_list() for t in tensors] 
    max_rank = max([len(s) for s in shapes]) 
    # Rank equalize all the tensors 
    for index in range(len(shapes)): 
     shape = shapes[index] 
     if len(shape) == max_rank: 
      continue 

     tensor = tensors[index] 
     for _ in range(max_rank - len(shape)): 
      shape.insert(0, 1) 
      tensor = tf.expand_dims(tensor, axis = 0) 
     tensors[index] = tensor 

    # Ensure if broadcasting is possible 
    from collections import Counter 
    broadcast_shape = [] 
    for index in range(max_rank): 
     dimensions = [s[index] for s in shapes] 
     repeats = Counter(dimensions) 
     if len(repeats) > 2 or (len(repeats) == 2 and \ 
          1 not in list(repeats.keys())): 
      raise Exception("Broadcasting not possible") 
     broadcast_shape.append(max(repeats.keys())) 

    # Broadcast the tensors 
    for axis, dimension in enumerate(broadcast_shape): 
     tensors = [tf.concat([t] * dimension, axis = axis) \ 
        if t.get_shape()[axis] == 1 else t for t in tensors] 

    return tensors 

出力：

x = tf.constant(1, shape = [10, 32, 1, 4, 4, 1]) 
y = tf.constant(1, shape =  [1, 32, 1, 4, 1]) 
z = tf.constant(1, shape =  [32, 4, 1, 1]) 
x, y, z = broadcast_tensors([x, y, z]) 
print(x.get_shape(), y.get_shape(), z.get_shape()) 
# (10, 32, 32, 4, 4, 1) (10, 32, 32, 4, 4, 1) (10, 32, 32, 4, 4, 1) 

x = tf.constant(1, shape = [10, 32, 1, 4, 4, 1]) 
y = tf.constant(1, shape =  [1, 32, 3, 4, 2]) 
z = tf.constant(1, shape =  [32, 3, 1, 3]) 
x, y, z = broadcast_tensors([x, y, z]) 
# Exception: Broadcasting not possible