ValueError: Shape must be rank 0 but is rank 1 for '{{node ReadFile}} = ReadFile[](args_0)' with input shapes: [?].
получил следующую ошибку tenorflow 2.0
import tensorflow as tf
def preprocessing(image):
print('preprocessing->',image)
image = tf.io.read_file(image)
#image = tf.image.decode_jpeg(img, channels=3)
#image = tf.cast(img, tf.float32)
return image
def train(ds):
for i, batch in enumerate(ds):
print("=====================batch{}====================={}".format(i,batch))
for x in batch:
print(x)
#print(x.numpy())
#print(x[1].numpy())
images = ['/media/jake/mark-4tb3/Screenshot_from_2020-02-19_23-05-22.png','/media/jake/mark-4tb3/Screenshot_from_2020-02-19_23-05-22.png','/media/jake/mark-4tb3/Screenshot_from_2020-02-19_23-05-22.png','/media/jake/mark-4tb3/Screenshot_from_2020-02-19_23-05-22.png']
images = tf.ragged.constant(images)
dataset = tf.data.Dataset.from_tensor_slices((images))
train(dataset.batch(2).map(preprocessing))
тогда вся ошибка
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-159-9b4a28882f72> in <module>
1 dataset = tf.data.Dataset.from_tensor_slices((images))
----> 2 train(dataset.batch(2).map(preprocessing))
~/venv/lib/python3.7/site-packages/tensorflow/python/data/ops/dataset_ops.py in map(self, map_func, num_parallel_calls, deterministic)
1619 """
1620 if num_parallel_calls is None:
-> 1621 return MapDataset(self, map_func, preserve_cardinality=True)
1622 else:
1623 return ParallelMapDataset(
~/venv/lib/python3.7/site-packages/tensorflow/python/data/ops/dataset_ops.py in __init__(self, input_dataset, map_func, use_inter_op_parallelism, preserve_cardinality, use_legacy_function)
3979 self._transformation_name(),
3980 dataset=input_dataset,
-> 3981 use_legacy_function=use_legacy_function)
3982 variant_tensor = gen_dataset_ops.map_dataset(
3983 input_dataset._variant_tensor, # pylint: disable=protected-access
~/venv/lib/python3.7/site-packages/tensorflow/python/data/ops/dataset_ops.py in __init__(self, func, transformation_name, dataset, input_classes, input_shapes, input_types, input_structure, add_to_graph, use_legacy_function, defun_kwargs)
3219 with tracking.resource_tracker_scope(resource_tracker):
3220 # TODO(b/141462134): Switch to using garbage collection.
-> 3221 self._function = wrapper_fn.get_concrete_function()
3222
3223 if add_to_graph:
~/venv/lib/python3.7/site-packages/tensorflow/python/eager/function.py in get_concrete_function(self, *args, **kwargs)
2530 """
2531 graph_function = self._get_concrete_function_garbage_collected(
-> 2532 *args, **kwargs)
2533 graph_function._garbage_collector.release() # pylint: disable=protected-access
2534 return graph_function
~/venv/lib/python3.7/site-packages/tensorflow/python/eager/function.py in _get_concrete_function_garbage_collected(self, *args, **kwargs)
2494 args, kwargs = None, None
2495 with self._lock:
-> 2496 graph_function, args, kwargs = self._maybe_define_function(args, kwargs)
2497 if self.input_signature:
2498 args = self.input_signature
~/venv/lib/python3.7/site-packages/tensorflow/python/eager/function.py in _maybe_define_function(self, args, kwargs)
2775
2776 self._function_cache.missed.add(call_context_key)
-> 2777 graph_function = self._create_graph_function(args, kwargs)
2778 self._function_cache.primary[cache_key] = graph_function
2779 return graph_function, args, kwargs
~/venv/lib/python3.7/site-packages/tensorflow/python/eager/function.py in _create_graph_function(self, args, kwargs, override_flat_arg_shapes)
2665 arg_names=arg_names,
2666 override_flat_arg_shapes=override_flat_arg_shapes,
-> 2667 capture_by_value=self._capture_by_value),
2668 self._function_attributes,
2669 # Tell the ConcreteFunction to clean up its graph once it goes out of
~/venv/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py in func_graph_from_py_func(name, python_func, args, kwargs, signature, func_graph, autograph, autograph_options, add_control_dependencies, arg_names, op_return_value, collections, capture_by_value, override_flat_arg_shapes)
979 _, original_func = tf_decorator.unwrap(python_func)
980
--> 981 func_outputs = python_func(*func_args, **func_kwargs)
982
983 # invariant: `func_outputs` contains only Tensors, CompositeTensors,
~/venv/lib/python3.7/site-packages/tensorflow/python/data/ops/dataset_ops.py in wrapper_fn(*args)
3212 attributes=defun_kwargs)
3213 def wrapper_fn(*args): # pylint: disable=missing-docstring
-> 3214 ret = _wrapper_helper(*args)
3215 ret = structure.to_tensor_list(self._output_structure, ret)
3216 return [ops.convert_to_tensor(t) for t in ret]
~/venv/lib/python3.7/site-packages/tensorflow/python/data/ops/dataset_ops.py in _wrapper_helper(*args)
3154 nested_args = (nested_args,)
3155
-> 3156 ret = autograph.tf_convert(func, ag_ctx)(*nested_args)
3157 # If `func` returns a list of tensors, `nest.flatten()` and
3158 # `ops.convert_to_tensor()` would conspire to attempt to stack
~/venv/lib/python3.7/site-packages/tensorflow/python/autograph/impl/api.py in wrapper(*args, **kwargs)
263 except Exception as e: # pylint:disable=broad-except
264 if hasattr(e, 'ag_error_metadata'):
--> 265 raise e.ag_error_metadata.to_exception(e)
266 else:
267 raise
ValueError: in user code:
<ipython-input-156-6db31559ad89>:5 preprocessing *
image = tf.io.read_file(image)
/home/jake/venv/lib/python3.7/site-packages/tensorflow/python/ops/gen_io_ops.py:568 read_file **
"ReadFile", filename=filename, name=name)
/home/jake/venv/lib/python3.7/site-packages/tensorflow/python/framework/op_def_library.py:744 _apply_op_helper
attrs=attr_protos, op_def=op_def)
/home/jake/venv/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py:595 _create_op_internal
compute_device)
/home/jake/venv/lib/python3.7/site-packages/tensorflow/python/framework/ops.py:3327 _create_op_internal
op_def=op_def)
/home/jake/venv/lib/python3.7/site-packages/tensorflow/python/framework/ops.py:1817 __init__
control_input_ops, op_def)
/home/jake/venv/lib/python3.7/site-packages/tensorflow/python/framework/ops.py:1657 _create_c_op
raise ValueError(str(e))
ValueError: Shape must be rank 0 but is rank 1 for '{{node ReadFile}} = ReadFile[](args_0)' with input shapes: [?].