我创建了一个非常复杂的keras模型，其中包含子模型以及一个与训练模型不同的推断模型（我仅使用训练模型的一部分来推断结果）是基于{{ 3}}。当我用它来预测值时，就可以获得正确的预测，并且一切正常。
但是，每次尝试进行培训时，我都会收到以下消息：
> --------------------------------------------------------------------------- InvalidArgumentError Traceback (most recent call
> last) <ipython-input-24-c3792779381d> in <module>
> 10 validation_steps=len(test_compares),
> 11
> ---> 12 epochs=50, nr_gpus=2
> 13 )
>
> /workdir/IQA/PIE+keras/model/PieAPPv0pt1_KERAS.py in train(self,
> optimizer, loss, generator, steps_per_epoch, validation_data,
> validation_steps, epochs, callbacks, train_features, nr_gpus)
> 251 train_multi = multi_gpu_model(train_model, gpus=nr_gpus)
> 252 train_multi.compile(optimizer=optimizer, loss=loss)
> --> 253 train_multi.fit_generator(generator=generator, steps_per_epoch=steps_per_epoch, epochs=epochs, callbacks=callbacks,
> validation_data=validation_data, validation_steps=validation_steps,
> shuffle=True)
> 254
> 255 else:
>
> /usr/local/lib/python3.6/dist-packages/keras/legacy/interfaces.py in
> wrapper(*args, **kwargs)
> 89 warnings.warn('Update your `' + object_name + '` call to the ' +
> 90 'Keras 2 API: ' + signature, stacklevel=2)
> ---> 91 return func(*args, **kwargs)
> 92 wrapper._original_function = func
> 93 return wrapper
>
> /usr/local/lib/python3.6/dist-packages/keras/engine/training.py in
> fit_generator(self, generator, steps_per_epoch, epochs, verbose,
> callbacks, validation_data, validation_steps, class_weight,
> max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)
> 1416 use_multiprocessing=use_multiprocessing, 1417
> shuffle=shuffle,
> -> 1418 initial_epoch=initial_epoch) 1419 1420 @interfaces.legacy_generator_methods_support
>
> /usr/local/lib/python3.6/dist-packages/keras/engine/training_generator.py
> in fit_generator(model, generator, steps_per_epoch, epochs, verbose,
> callbacks, validation_data, validation_steps, class_weight,
> max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)
> 215 outs = model.train_on_batch(x, y,
> 216 sample_weight=sample_weight,
> --> 217 class_weight=class_weight)
> 218
> 219 outs = to_list(outs)
>
> /usr/local/lib/python3.6/dist-packages/keras/engine/training.py in
> train_on_batch(self, x, y, sample_weight, class_weight) 1215
> ins = x + y + sample_weights 1216
> self._make_train_function()
> -> 1217 outputs = self.train_function(ins) 1218 return unpack_singleton(outputs) 1219
>
> /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py
> in __call__(self, inputs) 2713 return
> self._legacy_call(inputs) 2714
> -> 2715 return self._call(inputs) 2716 else: 2717 if py_any(is_tensor(x) for x in inputs):
>
> /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py
> in _call(self, inputs) 2673 fetched =
> self._callable_fn(*array_vals, run_metadata=self.run_metadata) 2674
> else:
> -> 2675 fetched = self._callable_fn(*array_vals) 2676 return fetched[:len(self.outputs)] 2677
>
> /usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py
> in __call__(self, *args, **kwargs) 1437 ret =
> tf_session.TF_SessionRunCallable( 1438
> self._session._session, self._handle, args, status,
> -> 1439 run_metadata_ptr) 1440 if run_metadata: 1441 proto_data =
> tf_session.TF_GetBuffer(run_metadata_ptr)
>
> /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/errors_impl.py
> in __exit__(self, type_arg, value_arg, traceback_arg)
> 526 None, None,
> 527 compat.as_text(c_api.TF_Message(self.status.status)),
> --> 528 c_api.TF_GetCode(self.status.status))
> 529 # Delete the underlying status object from memory otherwise it stays alive
> 530 # as there is a reference to status from this from the traceback due to
>
> InvalidArgumentError: You must feed a value for placeholder tensor
> 'input_ref' with dtype float and shape [?,?,?,3] [[{{node
> input_ref}}]] [[{{node
> training/Adam/gradients/loss/score_AB_loss/sub_grad/Reshape}}]]
我已经验证了生成器，并且一切正常。尽管如此，我还尝试从模型中获取张量作为输出，然后使用K.eval()和tf.eval(session=K.get_session())在keras后端对其进行评估。在这两种情况下，我都收到以下消息：
> --------------------------------------------------------------------------- InvalidArgumentError Traceback (most recent call
> last)
> /usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py
> in _do_call(self, fn, *args) 1333 try:
> -> 1334 return fn(*args) 1335 except errors.OpError as e:
>
> /usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py
> in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
> 1318 return self._call_tf_sessionrun(
> -> 1319 options, feed_dict, fetch_list, target_list, run_metadata) 1320
>
> /usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py
> in _call_tf_sessionrun(self, options, feed_dict, fetch_list,
> target_list, run_metadata) 1406 self._session, options,
> feed_dict, fetch_list, target_list,
> -> 1407 run_metadata) 1408
>
> InvalidArgumentError: You must feed a value for placeholder tensor
> 'input_ref' with dtype float and shape [?,?,?,3] [[{{node
> input_ref}}]] [[{{node compute_scores/lambda_7/truediv}}]]
>
> During handling of the above exception, another exception occurred:
>
> InvalidArgumentError Traceback (most recent call
> last) <ipython-input-18-c2f5a14e61a1> in <module>
> 1 import keras.backend as K
> 2
> ----> 3 K.eval(pred[0])
>
> /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py
> in eval(x)
> 671 ```
> 672 """
> --> 673 return to_dense(x).eval(session=get_session())
> 674
> 675
>
> /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py
> in eval(self, feed_dict, session)
> 693
> 694 """
> --> 695 return _eval_using_default_session(self, feed_dict, self.graph, session)
> 696
> 697
>
> /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py
> in _eval_using_default_session(tensors, feed_dict, graph, session)
> 5179 "the tensor's graph is different from the
> session's " 5180 "graph.")
> -> 5181 return session.run(tensors, feed_dict) 5182 5183
>
> /usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py
> in run(self, fetches, feed_dict, options, run_metadata)
> 927 try:
> 928 result = self._run(None, fetches, feed_dict, options_ptr,
> --> 929 run_metadata_ptr)
> 930 if run_metadata:
> 931 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
>
> /usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py
> in _run(self, handle, fetches, feed_dict, options, run_metadata)
> 1150 if final_fetches or final_targets or (handle and
> feed_dict_tensor): 1151 results = self._do_run(handle,
> final_targets, final_fetches,
> -> 1152 feed_dict_tensor, options, run_metadata) 1153 else: 1154 results = []
>
> /usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py
> in _do_run(self, handle, target_list, fetch_list, feed_dict, options,
> run_metadata) 1326 if handle is None: 1327 return
> self._do_call(_run_fn, feeds, fetches, targets, options,
> -> 1328 run_metadata) 1329 else: 1330 return self._do_call(_prun_fn, handle, feeds, fetches)
>
> /usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py
> in _do_call(self, fn, *args) 1346 pass 1347
> message = error_interpolation.interpolate(message, self._graph)
> -> 1348 raise type(e)(node_def, op, message) 1349 1350 def _extend_graph(self):
>
> InvalidArgumentError: You must feed a value for placeholder tensor
> 'input_ref' with dtype float and shape [?,?,?,3] [[node input_ref
> (defined at
> /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:517)
> ]] [[node compute_scores/lambda_7/truediv (defined at
> /workdir/IQA/PIE+keras/model/PieAPPv0pt1_KERAS.py:133) ]]
>
> Caused by op 'input_ref', defined at: File
> "/usr/lib/python3.6/runpy.py", line 193, in _run_module_as_main
> "__main__", mod_spec) File "/usr/lib/python3.6/runpy.py", line 85, in _run_code
> exec(code, run_globals) File "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py", line
> 16, in <module>
> app.launch_new_instance() File "/usr/local/lib/python3.6/dist-packages/traitlets/config/application.py",
> line 664, in launch_instance
> app.start() File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelapp.py", line
> 563, in start
> self.io_loop.start() File "/usr/local/lib/python3.6/dist-packages/tornado/platform/asyncio.py",
> line 148, in start
> self.asyncio_loop.run_forever() File "/usr/lib/python3.6/asyncio/base_events.py", line 438, in run_forever
> self._run_once() File "/usr/lib/python3.6/asyncio/base_events.py", line 1451, in _run_once
> handle._run() File "/usr/lib/python3.6/asyncio/events.py", line 145, in _run
> self._callback(*self._args) File "/usr/local/lib/python3.6/dist-packages/tornado/ioloop.py", line 690,
> in <lambda>
> lambda f: self._run_callback(functools.partial(callback, future)) File "/usr/local/lib/python3.6/dist-packages/tornado/ioloop.py", line
> 743, in _run_callback
> ret = callback() File "/usr/local/lib/python3.6/dist-packages/tornado/gen.py", line 787, in
> inner
> self.run() File "/usr/local/lib/python3.6/dist-packages/tornado/gen.py", line 748, in
> run
> yielded = self.gen.send(value) File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelbase.py", line
> 361, in process_one
> yield gen.maybe_future(dispatch(*args)) File "/usr/local/lib/python3.6/dist-packages/tornado/gen.py", line 209, in
> wrapper
> yielded = next(result) File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelbase.py", line
> 268, in dispatch_shell
> yield gen.maybe_future(handler(stream, idents, msg)) File "/usr/local/lib/python3.6/dist-packages/tornado/gen.py", line 209, in
> wrapper
> yielded = next(result) File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelbase.py", line
> 541, in execute_request
> user_expressions, allow_stdin, File "/usr/local/lib/python3.6/dist-packages/tornado/gen.py", line 209, in
> wrapper
> yielded = next(result) File "/usr/local/lib/python3.6/dist-packages/ipykernel/ipkernel.py", line
> 300, in do_execute
> res = shell.run_cell(code, store_history=store_history, silent=silent) File
> "/usr/local/lib/python3.6/dist-packages/ipykernel/zmqshell.py", line
> 536, in run_cell
> return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs) File
> "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py",
> line 2848, in run_cell
> raw_cell, store_history, silent, shell_futures) File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py",
> line 2874, in _run_cell
> return runner(coro) File "/usr/local/lib/python3.6/dist-packages/IPython/core/async_helpers.py",
> line 68, in _pseudo_sync_runner
> coro.send(None) File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py",
> line 3051, in run_cell_async
> interactivity=interactivity, compiler=compiler, result=result) File
> "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py",
> line 3242, in run_ast_nodes
> if (await self.run_code(code, result, async_=asy)): File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py",
> line 3319, in run_code
> exec(code_obj, self.user_global_ns, self.user_ns) File "<ipython-input-10-2df6f0aeb9af>", line 1, in <module>
> pieModel = PieAPP('pieModel.p') # File "/workdir/IQA/PIE+keras/model/PieAPPv0pt1_KERAS.py", line 23, in
> __init__
> self.compute_scores = self._build_compute_scores() File "/workdir/IQA/PIE+keras/model/PieAPPv0pt1_KERAS.py", line 82, in
> _build_compute_scores
> img_ref = L.Input((None,None,3), name='input_ref') File "/usr/local/lib/python3.6/dist-packages/keras/engine/input_layer.py",
> line 178, in Input
> input_tensor=tensor) File "/usr/local/lib/python3.6/dist-packages/keras/legacy/interfaces.py",
> line 91, in wrapper
> return func(*args, **kwargs) File "/usr/local/lib/python3.6/dist-packages/keras/engine/input_layer.py",
> line 87, in __init__
> name=self.name) File "/usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py",
> line 517, in placeholder
> x = tf.placeholder(dtype, shape=shape, name=name) File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/array_ops.py",
> line 2077, in placeholder
> return gen_array_ops.placeholder(dtype=dtype, shape=shape, name=name) File
> "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/gen_array_ops.py",
> line 5791, in placeholder
> "Placeholder", dtype=dtype, shape=shape, name=name) File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/op_def_library.py",
> line 788, in _apply_op_helper
> op_def=op_def) File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/deprecation.py",
> line 507, in new_func
> return func(*args, **kwargs) File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py",
> line 3300, in create_op
> op_def=op_def) File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py",
> line 1801, in __init__
> self._traceback = tf_stack.extract_stack()
>
> InvalidArgumentError (see above for traceback): You must feed a value
> for placeholder tensor 'input_ref' with dtype float and shape
> [?,?,?,3] [[node input_ref (defined at
> /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:517)
> ]] [[node compute_scores/lambda_7/truediv (defined at
> /workdir/IQA/PIE+keras/model/PieAPPv0pt1_KERAS.py:133) ]]
所以，我的问题是：我做错了什么？为什么我可以使用model.predict()并获得正确的结果，但是从模型中捕获输出张量并在K.eval()上进行评估（或尝试训练模型）时，我得到了第一条错误消息？ >