Tensorflow 2 Object Detection API: Numpy Version Errors

Question

I followed the "Training Custom Object Detector" tutorial (https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/latest/training.html)

When running the script to continue training a pre-trained model:

python model_main_tf2.py --model_dir=models/my_ssd_resnet50_v1_fpn --pipeline_config_path=models/my_ssd_resnet50_v1_fpn/pipeline.config

(found here: https://github.com/tensorflow/models/blob/master/research/object_detection/model_main_tf2.py)

Using different numpy versions, I get the following errors.

Scenario #1:

tensorflow: 2.2.0
numpy: 1.20.0-1

NotImplementedError: Cannot convert a symbolic Tensor (cond_2/strided_slice:0) to a numpy array. This error may indicate that you're trying to pass a Tensor to a NumPy call, which is not supported

I looked online and it suggests to downgrade the numpy version < 1.20.0 (NotImplementedError: Cannot convert a symbolic Tensor (2nd_target:0) to a numpy array). Note, the version numpy version must be >= 1.19.2 for tensorflow 2.2.0.

Scenario #2:

tensorflow: 2.2.0
numpy: 1.19.2-5

ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject

However, the online recommendation is to upgrade numpy to >= 1.20.0. (ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject). There is a github issue related to this: https://github.com/tensorflow/models/issues/9749.

I'm not sure what version to use to get the code running.

Appendix: Scenario #1 Error Code (numpy: 1.20.0-1)

  File "model_main_tf2.py", line 113, in <module>
    tf.compat.v1.app.run()
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\platform\app.py", line 40, in run
    _run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\absl\app.py", line 303, in run
    _run_main(main, args)
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\absl\app.py", line 251, in _run_main
    sys.exit(main(argv))
  File "model_main_tf2.py", line 104, in main
    model_lib_v2.train_loop(
  File "C:\Users\212765830\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\object_detection\model_lib_v2.py", line 530, in train_loop
    train_input = strategy.experimental_distribute_datasets_from_function(
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\util\deprecation.py", line 340, in new_func
    return func(*args, **kwargs)
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\distribute\distribute_lib.py", line 1143, in experimental_distribute_datasets_from_function
    return self.distribute_datasets_from_function(dataset_fn, options)
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\distribute\distribute_lib.py", line 1134, in distribute_datasets_from_function
    return self._extended._distribute_datasets_from_function(  # pylint: disable=protected-access
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\distribute\mirrored_strategy.py", line 545, in _distribute_datasets_from_function
    return input_lib.get_distributed_datasets_from_function(
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\distribute\input_lib.py", line 161, in get_distributed_datasets_from_function
    return DistributedDatasetsFromFunction(dataset_fn, input_workers,
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\distribute\input_lib.py", line 1272, in __init__
    _create_datasets_from_function_with_input_context(
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\distribute\input_lib.py", line 1936, in _create_datasets_from_function_with_input_context
    dataset = dataset_fn(ctx)
  File "C:\Users\212765830\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\object_detection\model_lib_v2.py", line 521, in train_dataset_fn
    train_input = inputs.train_input(
  File "C:\Users\212765830\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\object_detection\inputs.py", line 893, in train_input
    dataset = INPUT_BUILDER_UTIL_MAP['dataset_build'](
  File "C:\Users\212765830\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\object_detection\builders\dataset_builder.py", line 251, in build
    dataset = dataset_map_fn(dataset, decoder.decode, batch_size,
  File "C:\Users\212765830\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\object_detection\builders\dataset_builder.py", line 236, in dataset_map_fn
    dataset = dataset.map_with_legacy_function(
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\util\deprecation.py", line 340, in new_func
    return func(*args, **kwargs)
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 2679, in map_with_legacy_function
    ParallelMapDataset(
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 4242, in __init__
    self._map_func = StructuredFunctionWrapper(
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 3493, in __init__
    self._function.add_to_graph(ops.get_default_graph())
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\framework\function.py", line 546, in add_to_graph
    self._create_definition_if_needed()
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\framework\function.py", line 378, in _create_definition_if_needed
    self._create_definition_if_needed_impl()
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\framework\function.py", line 400, in _create_definition_if_needed_impl
    temp_graph = func_graph_from_py_func(
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\framework\function.py", line 971, in func_graph_from_py_func
    outputs = func(*func_graph.inputs)
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 3485, in wrapper_fn
    ret = _wrapper_helper(*args)
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 3453, in _wrapper_helper
    ret = autograph.tf_convert(func, ag_ctx)(*nested_args)
  File "C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\autograph\impl\api.py", line 670, in wrapper
    raise e.ag_error_metadata.to_exception(e)
NotImplementedError: in user code:

    C:\Users\212765830\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\object_detection\data_decoders\tf_example_decoder.py:524 default_groundtruth_weights  *
        [tf.shape(tensor_dict[fields.InputDataFields.groundtruth_boxes])[0]],
    C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\util\dispatch.py:201 wrapper  **
        return target(*args, **kwargs)
    C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\ops\array_ops.py:3120 ones
        output = _constant_if_small(one, shape, dtype, name)
    C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\ops\array_ops.py:2804 _constant_if_small
        if np.prod(shape) < 1000:
    <__array_function__ internals>:5 prod

    C:\Users\212765830\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\numpy\core\fromnumeric.py:3030 prod
        return _wrapreduction(a, np.multiply, 'prod', axis, dtype, out,
    C:\Users\212765830\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\numpy\core\fromnumeric.py:87 _wrapreduction
        return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
    C:\Users\212765830\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\framework\ops.py:852 __array__
        raise NotImplementedError(
NotImplementedError: Cannot convert a symbolic Tensor (cond_2/strided_slice:0) to a numpy array. This error may indicate that you're trying to pass a Tensor to a NumPy call, which is not supported

Scenario #2 Error Code (numpy: 1.19.2-5)

2021-02-25 09:59:47.039105: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2021-02-25 09:59:47.044310: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
Traceback (most recent call last):
  File "model_main_tf2.py", line 32, in <module>
    from object_detection import model_lib_v2
  File "C:\Users\212765830\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\object_detection\model_lib_v2.py", line 29, in <module>
    from object_detection import eval_util
  File "C:\Users\212765830\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\object_detection\eval_util.py", line 35, in <module>
    from object_detection.metrics import coco_evaluation
  File "C:\Users\212765830\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\object_detection\metrics\coco_evaluation.py", line 25, in <module>
    from object_detection.metrics import coco_tools
  File "C:\Users\212765830\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\object_detection\metrics\coco_tools.py", line 51, in <module>
    from pycocotools import coco
  File "C:\Users\212765830\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\pycocotools\coco.py", line 56, in <module>
    from . import mask as maskUtils
  File "C:\Users\212765830\AppData\Local\Continuum\anaconda3\envs\tensorflow\lib\site-packages\pycocotools\mask.py", line 3, in <module>
    import pycocotools._mask as _mask
  File "pycocotools\_mask.pyx", line 1, in init pycocotools._mask
ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject```

Gabriel · Accepted Answer · 2021-03-05 02:48:57Z

10

I had this same issue:

NotImplementedError: Cannot convert a symbolic Tensor (cond_2/strided_slice:0) to a numpy array. This error may indicate that you're trying to pass a Tensor to a NumPy call, which is not supported

The problem was fixed by changing np.prod for reduce_prod in this function https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/ops/array_ops.py

def _constant_if_small(value, shape, dtype, name):
  try:
    if np.prod(shape) < 1000:
      return constant(value, shape=shape, dtype=dtype, name=name)
  except TypeError:
    # Happens when shape is a Tensor, list with Tensor elements, etc.
    pass
  return None

Note that you need to import reduce_prod at the top:

from tensorflow.math import reduce_prod

answered Mar 5, 2021 at 2:48

Gabriel

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3 Comments

Keith Rush Over a year ago

Excellent finding! Do you think you could open up a PR on TensorFlow for this? It seems like this is still an issue

arunvg Over a year ago

Thank you . Saved the day. Could solve it from the above with import modified as "from tensorflow.python.ops.math_ops import reduce_prod"

jnroche Over a year ago

It works on Python v 3.8.8, tensorflow v 2.3.0 and Numpy v1.20.1 and jupyter core v 4.7.1 thank you very much!

HannahW · Accepted Answer · 2021-02-26 09:25:41Z

6

I had the same error. Are you on windows? If so try (that worked for me):
pip uninstall pycocotools
pip install pycocotools-windows

answered Feb 26, 2021 at 9:25

HannahW

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2 Comments

Phillip Ng Over a year ago

Yes, that worked! And yes, I was running on Windows.

Mansi Over a year ago

Any idea what would work for macOS users?

Royce Schultz · Accepted Answer · 2021-03-19 03:27:46Z

5

I had this issue on MacOS. I fixed it by installing an older version of pycocotools.

pip install pycocotools==2.0.0

answered Mar 19, 2021 at 3:27

Royce Schultz

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1 Comment

Josh Over a year ago

Thanks for this. I'm trying to run the tflite_model_maker examples using python 3.7 (as per colab). For some reason 2.0.2 worked fine on Windows with numpy==1.19.5, but on Ubuntu I needed to downgrade to 2.0.0

Eddy Piedad · Accepted Answer · 2021-04-28 14:25:02Z

2

I have the same problem and I downgraded my numpy from 1.20.2 to 1.19.5, now it´s working.

pip install numpy==1.19.5

You can check the trend here: https://github.com/tensorflow/models/issues/9706

answered Apr 28, 2021 at 14:25

Eddy Piedad

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