InvalidArgumentError: slice index xxx of dimension xxx out of bounds
InvalidArgumentError: slice index xxx of dimension xxx out of bounds
- 發生原因
- 解決辦法
- 完整Traceback
- 參考連結
發生原因
這是在調用Mask_RCNN中的run_graph時所發生的錯誤。此處有用到的run_graph是經筆者修改過後，可以在"training"模式下運行的版本，詳見run_graph at training mode.
在config中宣告BATCH_SIZE為4，因此在調用模型的時候，必須確保輸入的數據符合這個條件。
model = modellib.MaskRCNN(mode="training", config=config,
model_dir=MODEL_DIR) #此處config中的BATCH_SIZE為4
一開始筆者疏忽，使用第0維全為1的輸入:
print(image.shape, image_meta.shape, rpn_match.shape, rpn_bbox.shape, gt_class_ids.shape, gt_boxes.shape, gt_masks.shape)
# (1, 576, 576, 3) (1, 18) (1, 82863, 1) (1, 256, 4) (1, 0) (1, 0, 4) (1, 576, 576, 0)
這導致文末InvalidArgumentError: slice index xxx of dimension xxx out of bounds的錯誤發生。
解決辦法
後來將輸入的第0維全部修改成4：
print(image.shape, image_meta.shape, rpn_match.shape, rpn_bbox.shape, gt_class_ids.shape, gt_boxes.shape, gt_masks.shape)
# (4, 576, 576, 3) (4, 18) (4, 82863, 1) (4, 256, 4) (4, 0) (4, 0, 4) (4, 576, 576, 0)
run_graph()便可成功運行：
model = modellib.MaskRCNN(mode="training", config=config,
model_dir=MODEL_DIR) #此處config中的BATCH_SIZE為4
pillar = model.keras_model.get_layer("ROI").output # node to start searching from
graph = model.run_graph([image, image_meta, rpn_match, rpn_bbox, gt_class_ids, gt_boxes, gt_masks], [
("rpn_class", model.keras_model.get_layer("rpn_class").output),
("rpn_bbox", model.keras_model.get_layer("rpn_bbox").output),
("pillar", pillar),
("pre_nms_anchors", model.ancestor(pillar, "ROI/pre_nms_anchors:0")),
("refined_anchors", model.ancestor(pillar, "ROI/refined_anchors:0")),
("refined_anchors_clipped", model.ancestor(pillar, "ROI/refined_anchors_clipped:0")),
("rois", tf.get_default_graph().get_tensor_by_name("proposal_targets/rois:0")),
("target_class_ids", tf.get_default_graph().get_tensor_by_name("proposal_targets/target_class_ids:0")),
("target_bbox", tf.get_default_graph().get_tensor_by_name("proposal_targets/target_bbox:0")),
("target_mask", tf.get_default_graph().get_tensor_by_name("proposal_targets/target_mask:0")),
("top_anchors", model.ancestor(pillar, "ROI/top_anchors:1")),
("proposals", model.keras_model.get_layer("ROI").output),
("mrcnn_class_logits", model.keras_model.get_layer("mrcnn_class_logits").output),
("mrcnn_class", model.keras_model.get_layer("mrcnn_class").output),
("mrcnn_bbox", model.keras_model.get_layer("mrcnn_bbox").output),
("rpn_class_loss", model.keras_model.get_layer("rpn_class_loss").output),
("rpn_bbox_loss", model.keras_model.get_layer("rpn_bbox_loss").output),
("mrcnn_class_loss", model.keras_model.get_layer("mrcnn_class_loss").output),
("mrcnn_bbox_loss", model.keras_model.get_layer("mrcnn_bbox_loss").output),
("mrcnn_mask_loss", model.keras_model.get_layer("mrcnn_mask_loss").output),
("target_class_ids", model.keras_model.get_layer("proposal_targets").output[1]),
("target_bbox", model.keras_model.get_layer("proposal_targets").output[2]),
("target_mask", model.keras_model.get_layer("proposal_targets").output[3])
])
"""
result:
rpn_class shape: (4, 82863, 2) min: 0.00000 max: 1.00000 float32
rpn_bbox shape: (4, 82863, 4) min: -36.51252 max: 63.45781 float32
pillar shape: (4, 2000, 4) min: 0.00000 max: 1.00000 float32
pre_nms_anchors shape: (4, 6000, 4) min: -0.00123 max: 0.91898 float32
refined_anchors shape: (4, 6000, 4) min: -24.39013 max: 24.44984 float32
refined_anchors_clipped shape: (4, 6000, 4) min: 0.00000 max: 1.00000 float32
rois shape: (4, 32, 4) min: 0.00000 max: 0.00000 float32
target_class_ids shape: (4, 32) min: 0.00000 max: 0.00000 int32
target_bbox shape: (4, 32, 4) min: 0.00000 max: 0.00000 float32
target_mask shape: (4, 32, 28, 28) min: 0.00000 max: 0.00000 float32
top_anchors shape: (4, 6000) min: 11.00000 max: 20525.00000 int32
proposals shape: (4, 2000, 4) min: 0.00000 max: 1.00000 float32
mrcnn_class_logits shape: (4, 32, 6) min: -2.87763 max: 3.33817 float32
mrcnn_class shape: (4, 32, 6) min: 0.00174 max: 0.86989 float32
mrcnn_bbox shape: (4, 32, 6, 4) min: -6.20270 max: 6.32315 float32
rpn_class_loss shape: () min: 8.17014 max: 8.17014 float32
rpn_bbox_loss shape: () min: 0.00000 max: 0.00000 float32
mrcnn_class_loss shape: () min: 0.00000 max: 0.00000 float32
mrcnn_bbox_loss shape: () min: 0.00000 max: 0.00000 float32
mrcnn_mask_loss shape: () min: 0.00000 max: 0.00000 float32
"""
完整Traceback
InvalidArgumentErrorTraceback (most recent call last)
/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1321 try:
-> 1322 return fn(*args)
1323 except errors.OpError as e:
/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
1306 return self._call_tf_sessionrun(
-> 1307 options, feed_dict, fetch_list, target_list, run_metadata)
1308
/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
1408 self._session, options, feed_dict, fetch_list, target_list,
-> 1409 run_metadata)
1410 else:
InvalidArgumentError: slice index 2 of dimension 0 out of bounds.
[[Node: proposal_targets/strided_slice_77 = StridedSlice[Index=DT_INT32, T=DT_BOOL, begin_mask=0, ellipsis_mask=0, end_mask=0, new_axis_mask=0, shrink_axis_mask=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](_arg_input_gt_masks_0_2, proposal_targets/strided_slice_40/stack_1, proposal_targets/strided_slice_77/stack_1, proposal_targets/strided_slice_3/stack_1)]]
During handling of the above exception, another exception occurred:
InvalidArgumentErrorTraceback (most recent call last)
in
74 ("target_class_ids", model.keras_model.get_layer("proposal_targets").output[1]),
75 ("target_bbox", model.keras_model.get_layer("proposal_targets").output[2]),
---> 76 ("target_mask", model.keras_model.get_layer("proposal_targets").output[3])
77 ])
/notebooks/Lorenzo/Mask_RCNN/mrcnn/model_allow_bg.py in run_graph(self, inputs, outputs)
2923 # outputs_np = samplewise_function(lcn, inputs, batch_size=4)
2924 # outputs_np = batchwise_function(lcn, inputs, batch_size=4)
-> 2925 outputs_np = kf(model_in)
2926
2927 # Pack the generated Numpy arrays into a a dict and log the results.
/usr/local/lib/python3.5/dist-packages/keras/backend/tensorflow_backend.py in __call__(self, inputs)
2473 session = get_session()
2474 updated = session.run(fetches=fetches, feed_dict=feed_dict,
-> 2475 **self.session_kwargs)
2476 return updated[:len(self.outputs)]
2477
/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
898 try:
899 result = self._run(None, fetches, feed_dict, options_ptr,
--> 900 run_metadata_ptr)
901 if run_metadata:
902 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1133 if final_fetches or final_targets or (handle and feed_dict_tensor):
1134 results = self._do_run(handle, final_targets, final_fetches,
-> 1135 feed_dict_tensor, options, run_metadata)
1136 else:
1137 results = []
/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1314 if handle is None:
1315 return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1316 run_metadata)
1317 else:
1318 return self._do_call(_prun_fn, handle, feeds, fetches)
/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1333 except KeyError:
1334 pass
-> 1335 raise type(e)(node_def, op, message)
1336
1337 def _extend_graph(self):
InvalidArgumentError: slice index 2 of dimension 0 out of bounds.
[[Node: proposal_targets/strided_slice_77 = StridedSlice[Index=DT_INT32, T=DT_BOOL, begin_mask=0, ellipsis_mask=0, end_mask=0, new_axis_mask=0, shrink_axis_mask=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](_arg_input_gt_masks_0_2, proposal_targets/strided_slice_40/stack_1, proposal_targets/strided_slice_77/stack_1, proposal_targets/strided_slice_3/stack_1)]]
Caused by op 'proposal_targets/strided_slice_77', defined at:
File "/usr/lib/python3.5/runpy.py", line 184, in _run_module_as_main
"__main__", mod_spec)
File "/usr/lib/python3.5/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/usr/local/lib/python3.5/dist-packages/ipykernel_launcher.py", line 16, in
app.launch_new_instance()
File "/usr/local/lib/python3.5/dist-packages/traitlets/config/application.py", line 658, in launch_instance
app.start()
File "/usr/local/lib/python3.5/dist-packages/ipykernel/kernelapp.py", line 505, in start
self.io_loop.start()
File "/usr/local/lib/python3.5/dist-packages/tornado/platform/asyncio.py", line 132, in start
self.asyncio_loop.run_forever()
File "/usr/lib/python3.5/asyncio/base_events.py", line 345, in run_forever
self._run_once()
File "/usr/lib/python3.5/asyncio/base_events.py", line 1312, in _run_once
handle._run()
File "/usr/lib/python3.5/asyncio/events.py", line 125, in _run
self._callback(*self._args)
File "/usr/local/lib/python3.5/dist-packages/tornado/ioloop.py", line 758, in _run_callback
ret = callback()
File "/usr/local/lib/python3.5/dist-packages/tornado/stack_context.py", line 300, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/tornado/gen.py", line 1233, in inner
self.run()
File "/usr/local/lib/python3.5/dist-packages/tornado/gen.py", line 1147, in run
yielded = self.gen.send(value)
File "/usr/local/lib/python3.5/dist-packages/ipykernel/kernelbase.py", line 370, in dispatch_queue
yield self.process_one()
File "/usr/local/lib/python3.5/dist-packages/tornado/gen.py", line 346, in wrapper
runner = Runner(result, future, yielded)
File "/usr/local/lib/python3.5/dist-packages/tornado/gen.py", line 1080, in __init__
self.run()
File "/usr/local/lib/python3.5/dist-packages/tornado/gen.py", line 1147, in run
yielded = self.gen.send(value)
File "/usr/local/lib/python3.5/dist-packages/ipykernel/kernelbase.py", line 357, in process_one
yield gen.maybe_future(dispatch(*args))
File "/usr/local/lib/python3.5/dist-packages/tornado/gen.py", line 326, in wrapper
yielded = next(result)
File "/usr/local/lib/python3.5/dist-packages/ipykernel/kernelbase.py", line 267, in dispatch_shell
yield gen.maybe_future(handler(stream, idents, msg))
File "/usr/local/lib/python3.5/dist-packages/tornado/gen.py", line 326, in wrapper
yielded = next(result)
File "/usr/local/lib/python3.5/dist-packages/ipykernel/kernelbase.py", line 534, in execute_request
user_expressions, allow_stdin,
File "/usr/local/lib/python3.5/dist-packages/tornado/gen.py", line 326, in wrapper
yielded = next(result)
File "/usr/local/lib/python3.5/dist-packages/ipykernel/ipkernel.py", line 294, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/usr/local/lib/python3.5/dist-packages/ipykernel/zmqshell.py", line 536, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py", line 2817, in run_cell
raw_cell, store_history, silent, shell_futures)
File "/usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py", line 2843, in _run_cell
return runner(coro)
File "/usr/local/lib/python3.5/dist-packages/IPython/core/async_helpers.py", line 67, in _pseudo_sync_runner
coro.send(None)
File "/usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py", line 3018, in run_cell_async
interactivity=interactivity, compiler=compiler, result=result)
File "/usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py", line 3183, in run_ast_nodes
if (yield from self.run_code(code, result)):
File "/usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py", line 3265, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "", line 3, in
model_dir=MODEL_DIR)
File "/notebooks/Lorenzo/Mask_RCNN/mrcnn/model_allow_bg.py", line 2007, in __init__
self.keras_model = self.build(mode=mode, config=config)
File "/notebooks/Lorenzo/Mask_RCNN/mrcnn/model_allow_bg.py", line 2160, in build
target_rois, input_gt_class_ids, gt_boxes, input_gt_masks])
File "/usr/local/lib/python3.5/dist-packages/keras/engine/topology.py", line 617, in __call__
output = self.call(inputs, **kwargs)
File "/notebooks/Lorenzo/Mask_RCNN/mrcnn/model_allow_bg.py", line 697, in call
self.config.IMAGES_PER_GPU, names=names)
File "/notebooks/Lorenzo/Mask_RCNN/mrcnn/utils.py", line 829, in batch_slice
inputs_slice = [x[i] for x in inputs]
File "/notebooks/Lorenzo/Mask_RCNN/mrcnn/utils.py", line 829, in
inputs_slice = [x[i] for x in inputs]
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/array_ops.py", line 523, in _slice_helper
name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/array_ops.py", line 689, in strided_slice
shrink_axis_mask=shrink_axis_mask)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 8232, in strided_slice
name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 3414, in create_op
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 1740, in __init__
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
InvalidArgumentError (see above for traceback): slice index 2 of dimension 0 out of bounds.
[[Node: proposal_targets/strided_slice_77 = StridedSlice[Index=DT_INT32, T=DT_BOOL, begin_mask=0, ellipsis_mask=0, end_mask=0, new_axis_mask=0, shrink_axis_mask=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](_arg_input_gt_masks_0_2, proposal_targets/strided_slice_40/stack_1, proposal_targets/strided_slice_77/stack_1, proposal_targets/strided_slice_3/stack_1)]]
參考連結
解决问题tensorflow.python.framework.errors_impl.InvalidArgumentError: slice index 1 of dimension 0 out o