tensorflow
NotImplementedError: Cannot convert a symbolic Tensor (strided_slice:0) to a numpy array.
Prerequisites
Please answer the following questions for yourself before submitting an issue.
- [x] I am using the latest TensorFlow Model Garden release and TensorFlow 2.
- [x] I am reporting the issue to the correct repository. (Model Garden research directory)
- [x] I checked to make sure that this issue has not already been filed.
1. The entire URL of the file you are using
https://github.com/tensorflow/models/blob/master/research/object_detection/model_main_tf2.py
2. Describe the bug
I am trying to train object detection model for custom data using tutorial on link. I tested the for environment faults using https://github.com/tensorflow/models/blob/master/research/object_detection/builders/model_builder_tf2_test.py. All test passed. But when I put it for training the models gives out error. Logs:
2021-02-05 14:26:00.620416: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-02-05 14:26:03.557625: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-02-05 14:26:03.790381: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties:
pciBusID: 0002:00:00.0 name: Tesla M60 computeCapability: 5.2
coreClock: 1.1775GHz coreCount: 16 deviceMemorySize: 7.92GiB deviceMemoryBandwidth: 149.31GiB/s
2021-02-05 14:26:03.796912: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-02-05 14:26:03.805410: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-02-05 14:26:03.813387: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-02-05 14:26:03.817933: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-02-05 14:26:03.827291: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-02-05 14:26:03.834728: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-02-05 14:26:03.850086: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-02-05 14:26:03.857292: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2021-02-05 14:26:03.860948: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2021-02-05 14:26:03.875535: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x80ec5ff940 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2021-02-05 14:26:03.880482: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2021-02-05 14:26:03.885168: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties:
pciBusID: 0002:00:00.0 name: Tesla M60 computeCapability: 5.2
coreClock: 1.1775GHz coreCount: 16 deviceMemorySize: 7.92GiB deviceMemoryBandwidth: 149.31GiB/s
2021-02-05 14:26:03.891972: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-02-05 14:26:03.895720: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-02-05 14:26:03.899501: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-02-05 14:26:03.904606: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-02-05 14:26:03.908422: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-02-05 14:26:03.912343: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-02-05 14:26:03.916413: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-02-05 14:26:03.924000: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2021-02-05 14:26:04.700603: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength
1 edge matrix:
2021-02-05 14:26:04.704509: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0
2021-02-05 14:26:04.706737: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N
2021-02-05 14:26:04.726496: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 7048 MB memory) -> physical GPU (device: 0, name: Tesla M60, pci bus id: 0002:00:00.0, compute capability: 5.2)
2021-02-05 14:26:04.736932: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x810d9b6950 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2021-02-05 14:26:04.741982: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Tesla M60, Compute Capability 5.2
INFO:tensorflow:Using MirroredStrategy with devices ('/job:localhost/replica:0/task:0/device:GPU:0',)
I0205 14:26:04.749317 8188 mirrored_strategy.py:500] Using MirroredStrategy with devices ('/job:localhost/replica:0/task:0/device:GPU:0',)
INFO:tensorflow:Maybe overwriting train_steps: None
I0205 14:26:04.755326 8188 config_util.py:552] Maybe overwriting train_steps: None
INFO:tensorflow:Maybe overwriting use_bfloat16: False
I0205 14:26:04.755326 8188 config_util.py:552] Maybe overwriting use_bfloat16: False
INFO:tensorflow:Reading unweighted datasets: ['E:/DS_2020_Wildlife/Multi_Class_Classification/Tensorflow/workspace/annotations/train.record']
I0205 14:26:04.923312 8188 dataset_builder.py:163] Reading unweighted datasets: ['E:/DS_2020_Wildlife/Multi_Class_Classification/Tensorflow/workspace/annotations/train.record']
INFO:tensorflow:Reading record datasets for input file: ['E:/DS_2020_Wildlife/Multi_Class_Classification/Tensorflow/workspace/annotations/train.record']
I0205 14:26:04.926311 8188 dataset_builder.py:80] Reading record datasets for input file: ['E:/DS_2020_Wildlife/Multi_Class_Classification/Tensorflow/workspace/annotations/train.record']
INFO:tensorflow:Number of filenames to read: 1
I0205 14:26:04.926311 8188 dataset_builder.py:81] Number of filenames to read: 1
WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards.
W0205 14:26:04.926311 8188 dataset_builder.py:87] num_readers has been reduced to 1 to match input file shards.
WARNING:tensorflow:From E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\object_detection\builders\dataset_builder.py:101: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.experimental.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.experimental_deterministic`.
W0205 14:26:04.928313 8188 deprecation.py:317] From E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\object_detection\builders\dataset_builder.py:101: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.experimental.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.experimental_deterministic`.
WARNING:tensorflow:From E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\object_detection\builders\dataset_builder.py:236: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.data.Dataset.map()
W0205 14:26:04.952313 8188 deprecation.py:317] From E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\object_detection\builders\dataset_builder.py:236: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is
deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.data.Dataset.map()
Traceback (most recent call last):
File "model_main_tf2.py", line 115, in <module>
tf.compat.v1.app.run()
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\platform\app.py", line 40,
in run
_run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\absl\app.py", line 300, in run
_run_main(main, args)
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\absl\app.py", line 251, in _run_main
sys.exit(main(argv))
File "model_main_tf2.py", line 106, in main
model_lib_v2.train_loop(
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\object_detection\model_lib_v2.py", line 569,
in train_loop
load_fine_tune_checkpoint(detection_model,
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\object_detection\model_lib_v2.py", line 352,
in load_fine_tune_checkpoint
features, labels = iter(input_dataset).next()
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\distribute\input_lib.py", line 858, in __iter__
iterators, element_spec = _create_iterators_per_worker_with_input_context(
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\distribute\input_lib.py", line 1401, in _create_iterators_per_worker_with_input_context
dataset = dataset_fn(ctx)
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\object_detection\model_lib_v2.py", line 521,
in train_dataset_fn
train_input = inputs.train_input(
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\object_detection\inputs.py", line 893, in train_input
dataset = INPUT_BUILDER_UTIL_MAP['dataset_build'](
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\object_detection\builders\dataset_builder.py", line 251, in build
dataset = dataset_map_fn(dataset, decoder.decode, batch_size,
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\object_detection\builders\dataset_builder.py", line 236, in dataset_map_fn
dataset = dataset.map_with_legacy_function(
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\util\deprecation.py", line
324, in new_func
return func(*args, **kwargs)
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 2402, in map_with_legacy_function
ParallelMapDataset(
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 4016, in __init__
self._map_func = StructuredFunctionWrapper(
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 3196, in __init__
self._function.add_to_graph(ops.get_default_graph())
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\framework\function.py", line 544, in add_to_graph
self._create_definition_if_needed()
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\framework\function.py", line 376, in _create_definition_if_needed
self._create_definition_if_needed_impl()
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\framework\function.py", line 398, in _create_definition_if_needed_impl
temp_graph = func_graph_from_py_func(
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\framework\function.py", line 969, in func_graph_from_py_func
outputs = func(*func_graph.inputs)
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 3188, in wrapper_fn
ret = _wrapper_helper(*args)
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 3156, in _wrapper_helper
ret = autograph.tf_convert(func, ag_ctx)(*nested_args)
File "E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\autograph\impl\api.py", line 265, in wrapper
raise e.ag_error_metadata.to_exception(e)
NotImplementedError: in user code:
E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\object_detection\data_decoders\tf_example_decoder.py:524 default_groundtruth_weights *
[tf.shape(tensor_dict[fields.InputDataFields.groundtruth_boxes])[0]],
E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\ops\array_ops.py:2967 ones **
output = _constant_if_small(one, shape, dtype, name)
E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\ops\array_ops.py:2662 _constant_if_small
if np.prod(shape) < 1000:
<__array_function__ internals>:5 prod
E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\numpy\core\fromnumeric.py:3030 prod
return _wrapreduction(a, np.multiply, 'prod', axis, dtype, out,
E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\numpy\core\fromnumeric.py:87 _wrapreduction
return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
E:\DS_2020_Wildlife\Multi_Class_Classification\Tensorflow\venv\lib\site-packages\tensorflow\python\framework\ops.py:748 __array__
raise NotImplementedError("Cannot convert a symbolic Tensor ({}) to a numpy"
NotImplementedError: Cannot convert a symbolic Tensor (strided_slice:0) to a numpy array.
6. System information
- OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Windows Sever 2012
- TensorFlow installed from (source or binary): PIP
- TensorFlow version (use command below): 2.2
- Python version: 3.8
- CUDA/cuDNN version: 10.1
- GPU model and memory: Tesla M60
System information OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Archlinux TensorFlow installed from (source or binary): PIP TensorFlow version (use command below): 2.4.1 Python version: 3.8 CUDA/cuDNN version: cudaToolkit 10.1 cuDnn 7.6.5 GPU model and memory: Quadro M2000
I have the same error if I use numpy 1.20.0
NotImplementedError: Cannot convert a symbolic Tensor (cond_2/strided_slice:0) to a numpy array.
if I use numpy 1.19.5 I get
ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject
Tried with TF 2.2.2 as well in both cases same errors
fixed using python 3.6
Thank you @dademiller360 changing the Python version from 3.8 to 3.6 fixed the issue. @saikumarchalla Can you clarify if this is intended behavior or a bug? If it's not a bug you can close the issue.
I have the same problem but when I modify from Python 3.8.5 to 3.6 I get the following error:
Traceback (most recent call last):
File "D:\Maurice_Doc\AI\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 64, in
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "model_main_tf2.py", line 31, in
Failed to load the native TensorFlow runtime.
See https://www.tensorflow.org/install/errors
for some common reasons and solutions. Include the entire stack trace above this error message when asking for help.
Anybody know how to fix this issue?
Same issue, but when I switch to Python 3.6 and try to install the Tensorflow Object Detection API using the research/object_detection/packages/tf2/setup.py file, I get this error:
Traceback (most recent call last):
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\sandbox.py", line 152, in save_modules
yield saved
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\sandbox.py", line 193, in setup_context
yield
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\sandbox.py", line 254, in run_setup
_execfile(setup_script, ns)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\sandbox.py", line 43, in _execfile
exec(code, globals, locals)
File "C:\Users\tinyr\AppData\Local\Temp\easy_install-3subbki0\pandas-1.2.2\setup.py", line 761, in <module>
File "C:\Users\tinyr\AppData\Local\Temp\easy_install-3subbki0\pandas-1.2.2\setup.py", line 731, in setup_package
File "C:\Users\tinyr\AppData\Local\Temp\easy_install-3subbki0\pandas-1.2.2\setup.py", line 505, in maybe_cythonize
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\Cython\Build\Dependencies.py", line 1079, in cythonize
nthreads, initializer=_init_multiprocessing_helper)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\multiprocessing\context.py", line 119, in Pool
context=self.get_context())
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\multiprocessing\pool.py", line 174, in __init__
self._repopulate_pool()
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\multiprocessing\pool.py", line 239, in _repopulate_pool
w.start()
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\multiprocessing\process.py", line 105, in start
self._popen = self._Popen(self)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\multiprocessing\context.py", line 322, in _Popen
return Popen(process_obj)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\multiprocessing\popen_spawn_win32.py", line 43, in __init__
with open(wfd, 'wb', closefd=True) as to_child:
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\sandbox.py", line 421, in _open
if mode not in ('r', 'rt', 'rb', 'rU', 'U') and not self._ok(path):
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\sandbox.py", line 432, in _ok
realpath = os.path.normcase(os.path.realpath(path))
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\ntpath.py", line 548, in abspath
return normpath(_getfullpathname(path))
TypeError: _getfullpathname: path should be string, bytes or os.PathLike, not int
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "object_detection/packages/tf2/setup.py", line 43, in <module>
python_requires='>3.6',
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\__init__.py", line 153, in setup
return distutils.core.setup(**attrs)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\distutils\core.py", line 148, in setup
dist.run_commands()
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\distutils\dist.py", line 955, in run_commands
self.run_command(cmd)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\distutils\dist.py", line 974, in run_command
cmd_obj.run()
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\command\install.py", line 67, in run
self.do_egg_install()
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\command\install.py", line 117, in do_egg_install
cmd.run(show_deprecation=False)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\command\easy_install.py", line 408, in run
self.easy_install(spec, not self.no_deps)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\command\easy_install.py", line 650, in easy_install
return self.install_item(None, spec, tmpdir, deps, True)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\command\easy_install.py", line 697, in install_item
self.process_distribution(spec, dist, deps)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\command\easy_install.py", line 745, in process_distribution
[requirement], self.local_index, self.easy_install
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\pkg_resources\__init__.py", line 768, in resolve
replace_conflicting=replace_conflicting
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\pkg_resources\__init__.py", line 1051, in best_match
return self.obtain(req, installer)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\pkg_resources\__init__.py", line 1063, in obtain
return installer(requirement)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\command\easy_install.py", line 669, in easy_install
return self.install_item(spec, dist.location, tmpdir, deps)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\command\easy_install.py", line 695, in install_item
dists = self.install_eggs(spec, download, tmpdir)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\command\easy_install.py", line 890, in install_eggs
return self.build_and_install(setup_script, setup_base)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\command\easy_install.py", line 1162, in build_and_install
self.run_setup(setup_script, setup_base, args)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\command\easy_install.py", line 1146, in run_setup
run_setup(setup_script, args)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\sandbox.py", line 257, in run_setup
raise
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\contextlib.py", line 99, in __exit__
self.gen.throw(type, value, traceback)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\sandbox.py", line 193, in setup_context
yield
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\contextlib.py", line 99, in __exit__
self.gen.throw(type, value, traceback)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\sandbox.py", line 164, in save_modules
saved_exc.resume()
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\sandbox.py", line 139, in resume
raise exc.with_traceback(self._tb)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\sandbox.py", line 152, in save_modules
yield saved
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\sandbox.py", line 193, in setup_context
yield
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\sandbox.py", line 254, in run_setup
_execfile(setup_script, ns)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\sandbox.py", line 43, in _execfile
exec(code, globals, locals)
File "C:\Users\tinyr\AppData\Local\Temp\easy_install-3subbki0\pandas-1.2.2\setup.py", line 761, in <module>
File "C:\Users\tinyr\AppData\Local\Temp\easy_install-3subbki0\pandas-1.2.2\setup.py", line 731, in setup_package
File "C:\Users\tinyr\AppData\Local\Temp\easy_install-3subbki0\pandas-1.2.2\setup.py", line 505, in maybe_cythonize
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\Cython\Build\Dependencies.py", line 1079, in cythonize
nthreads, initializer=_init_multiprocessing_helper)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\multiprocessing\context.py", line 119, in Pool
context=self.get_context())
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\multiprocessing\pool.py", line 174, in __init__
self._repopulate_pool()
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\multiprocessing\pool.py", line 239, in _repopulate_pool
w.start()
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\multiprocessing\process.py", line 105, in start
self._popen = self._Popen(self)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\multiprocessing\context.py", line 322, in _Popen
return Popen(process_obj)
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\multiprocessing\popen_spawn_win32.py", line 43, in __init__
with open(wfd, 'wb', closefd=True) as to_child:
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\sandbox.py", line 421, in _open
if mode not in ('r', 'rt', 'rb', 'rU', 'U') and not self._ok(path):
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\site-packages\setuptools\sandbox.py", line 432, in _ok
realpath = os.path.normcase(os.path.realpath(path))
File "C:\Users\tinyr\anaconda3\envs\squirrel\lib\ntpath.py", line 548, in abspath
return normpath(_getfullpathname(path))
TypeError: _getfullpathname: path should be string, bytes or os.PathLike, not int
In the meantime I solve it by using colab for my object detection. But I would like to be able to use my pc as well
I have the same problem but when I modify from Python 3.8.5 to 3.6 I get the following error:
Traceback (most recent call last): File "D:\Maurice_Doc\AI\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 64, in from tensorflow.python._pywrap_tensorflow_internal import * ImportError: DLL load failed: The specified module could not be found.
During handling of the above exception, another exception occurred:
Traceback (most recent call last): File "model_main_tf2.py", line 31, in import tensorflow.compat.v2 as tf File "D:\Maurice_Doc\AI\anaconda3\envs\tensorflow\lib\site-packages\tensorflow__init__.py", line 41, in from tensorflow.python.tools import module_util as module_util File "D:\Maurice_Doc\AI\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python__init_.py", line 39, in from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow File "D:\Maurice_Doc\AI\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 83, in raise ImportError(msg) ImportError: Traceback (most recent call last): File "D:\Maurice_Doc\AI\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 64, in from tensorflow.python._pywrap_tensorflow_internal import * ImportError: DLL load failed: The specified module could not be found.
Failed to load the native TensorFlow runtime.
See https://www.tensorflow.org/install/errors
for some common reasons and solutions. Include the entire stack trace above this error message when asking for help.
Anybody know how to fix this issue?
Have you installed tensorflow correctly? This may be due to C++ executables not present in your system.
These are the results that I get when I lookup my tensorflow installation. Is there something that is missing?
These are the results that I get when I lookup my tensorflow installation. Is there something that is missing?
python -c "import tensorflow as tf;print(tf.reduce_sum(tf.random.normal([1000, 1000])))"
Can you check if this works?
If this works tensorflow is correctly installed. Else there is something wrong with tensorflow installation rather than object detection API.
This is the results I get:
I have the same error as what you are getting. im using numpy 1.20.0 with Tensorflow 2.4.1
I'm convinced that numpy is the problem but im honestly too new at training models and using TF etc. This is the tutorial ive been following https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/latest/training.html
Have you had any luck with solving this issue?
No, unfortunatly. Just using colab for the moment and hopping that the inference part of tensorflow object detection does work on my computer
This is the results I get:
I have the same error as what you are getting. im using numpy 1.20.0 with Tensorflow 2.4.1
I'm convinced that numpy is the problem but im honestly too new at training models and using TF etc. This is the tutorial ive been following https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/latest/training.html
Have you had any luck with solving this issue?
Try to downgrade numpy to numpy 1.19.5 pypi_0 pypi
pip install numpy==1.19.5
after that, check with conda list which numpy version you have installed
@dademiller360 The problem is if we do that we get the error mentioned earlier ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from. Some people are able to solve this by downgrading to Python 3.6. But if I do that I get the error from my first post:
Traceback (most recent call last): File "D:\Maurice_Doc\AI\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 64, in from tensorflow.python._pywrap_tensorflow_internal import * ImportError: DLL load failed: The specified module could not be found.
During handling of the above exception, another exception occurred:
Traceback (most recent call last): File "model_main_tf2.py", line 31, in import tensorflow.compat.v2 as tf File "D:\Maurice_Doc\AI\anaconda3\envs\tensorflow\lib\site-packages\tensorflow__init__.py", line 41, in from tensorflow.python.tools import module_util as module_util File "D:\Maurice_Doc\AI\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python__init_.py", line 39, in from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow File "D:\Maurice_Doc\AI\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 83, in raise ImportError(msg) ImportError: Traceback (most recent call last): File "D:\Maurice_Doc\AI\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 64, in from tensorflow.python._pywrap_tensorflow_internal import * ImportError: DLL load failed: The specified module could not be found.
Failed to load the native TensorFlow runtime.
See https://www.tensorflow.org/install/errors
for some common reasons and solutions. Include the entire stack trace above this error message when asking for help.
Hi @aniketbote I posted this answer in Stack Overflow: https://stackoverflow.com/questions/66373169/tensorflow-2-object-detection-api-numpy-version-errors/66486051#66486051
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 of the file:
from tensorflow.math import reduce_prod
@glemarivero
Hi @aniketbote I posted this answer in Stack Overflow: https://stackoverflow.com/questions/66373169/tensorflow-2-object-detection-api-numpy-version-errors/66486051#66486051
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.prodforreduce_prodin this function https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/ops/array_ops.pydef _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 NoneNote that you need to import
reduce_prodat the top of the file:from tensorflow.math import reduce_prod
I was able to fix issue like you described but by importing reduc_prod as:
from tensorflow.python.ops.math_ops import reduce_prod
...
Seems like it is a bug in tensorflow
@glemarivero
Hi @aniketbote I posted this answer in Stack Overflow: https://stackoverflow.com/questions/66373169/tensorflow-2-object-detection-api-numpy-version-errors/66486051#66486051 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.prodforreduce_prodin this function https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/ops/array_ops.pydef _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 NoneNote that you need to import
reduce_prodat the top of the file:from tensorflow.math import reduce_prodI was able to fix issue like you described but by importing
reduc_prodas:from tensorflow.python.ops.math_ops import reduce_prod ...Seems like it is a bug in
tensorflow
Hello, I'm new to tf object detection. I had the same error but after I changed import this error was gone out. But I got new error:
Fatal Python error: Aborted
Thread 0x00007f505b7fe700 (most recent call first): File "/usr/lib/python3.7/threading.py", line 296 in wait File "/usr/lib/python3.7/queue.py", line 170 in get File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/summary/writer/event_file_writer.py", line 159 in run File "/usr/lib/python3.7/threading.py", line 926 in _bootstrap_inner File "/usr/lib/python3.7/threading.py", line 890 in _bootstrap
Current thread 0x00007f50f699f740 (most recent call first):
File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 699 in init
File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 1585 in init
File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/training/session_manager.py", line 194 in _restore_checkpoint
File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/training/session_manager.py", line 290 in prepare_session
File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/training/supervisor.py", line 734 in prepare_or_wait_for_session
File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/training/supervisor.py", line 1003 in managed_session
File "/usr/lib/python3.7/contextlib.py", line 112 in enter
File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tf_slim/learning.py", line 745 in train
File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/object_detection-0.1-py3.7.egg/object_detection/legacy/trainer.py", line 415 in train
File "train.py", line 182 in main
File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/util/deprecation.py", line 324 in new_func
File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/absl/app.py", line 251 in _run_main
File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/absl/app.py", line 303 in run
File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/platform/app.py", line 40 in run
File "train.py", line 186 in
Did you face this probled before? Or do you have any idea about this error?
@glemarivero
Hi @aniketbote I posted this answer in Stack Overflow: https://stackoverflow.com/questions/66373169/tensorflow-2-object-detection-api-numpy-version-errors/66486051#66486051 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.prodforreduce_prodin this function https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/ops/array_ops.pydef _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 NoneNote that you need to import
reduce_prodat the top of the file:from tensorflow.math import reduce_prodI was able to fix issue like you described but by importing
reduc_prodas:from tensorflow.python.ops.math_ops import reduce_prod ...Seems like it is a bug in
tensorflowHello, I'm new to tf object detection. I had the same error but after I changed import this error was gone out. But I got new error:
Fatal Python error: Aborted
Thread 0x00007f505b7fe700 (most recent call first): File "/usr/lib/python3.7/threading.py", line 296 in wait File "/usr/lib/python3.7/queue.py", line 170 in get File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/summary/writer/event_file_writer.py", line 159 in run File "/usr/lib/python3.7/threading.py", line 926 in _bootstrap_inner File "/usr/lib/python3.7/threading.py", line 890 in _bootstrap
Current thread 0x00007f50f699f740 (most recent call first): File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 699 in init File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 1585 in init File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/training/session_manager.py", line 194 in _restore_checkpoint File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/training/session_manager.py", line 290 in prepare_session File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/training/supervisor.py", line 734 in prepare_or_wait_for_session File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/training/supervisor.py", line 1003 in managed_session File "/usr/lib/python3.7/contextlib.py", line 112 in enter File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tf_slim/learning.py", line 745 in train File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/object_detection-0.1-py3.7.egg/object_detection/legacy/trainer.py", line 415 in train File "train.py", line 182 in main File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/util/deprecation.py", line 324 in new_func File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/absl/app.py", line 251 in _run_main File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/absl/app.py", line 303 in run File "/home/vlad/.virtualenvs/tf1_obj_det_p37/lib/python3.7/site-packages/tensorflow_core/python/platform/app.py", line 40 in run File "train.py", line 186 in Aborted (core dumped)
Did you face this probled before? Or do you have any idea about this error?
I fixed this by adding CUDA_VISIBLE_DEVICES=""
@Pipickin But then you are running the training on CPU and not GPU. Were you able to train anything else? Just want to know if CUDA is setup correctly.
I had the same issue with newly installed tensorflow 2.2.0 and python 3.8.5. Installing tensorflow with pip will install numpy version 1.20.2. You can then downgrade numpy to version 1.18.4 (just uninstall with pip and install that particular version). Then everything works perfectly fine.
@glemarivero Hello. I trained my model via google colab, because I have not enough Capability on my GPU (I didn't even try do it). I was wondering why I got the error above
I had the same error. It is fixed per glemarivero's workaround. array_ops.py is inside ```C:\Users\xxxxxx\AppData\Local\Programs\Python\Python38\Lib\site-packages\tensorflow\python\ops'''. Somehow, I have to do it this way:
import tensorflow as tf
......
......
......
if tf.math.reduce_prod(shape) < 1000:
Try to downgrade numpy to numpy 1.19.5 pypi_0 pypi
pip install numpy==1.19.5this one fucking work
I have same error, Python 3.8.8, NumPy 1.20.2, TensorFlow 2.5.0
I have newest Arch linux with i3wm window manager, my processor is i5 8400 and my GPU is GTX 1070 8GB, I have 16GB of RAM AND I am trying to follow this tutorial and my .ipynb file is uploaded. (renamed to .txt, just rename it to .ipynb) Untitled.txt
My error:
NotImplementedError Traceback (most recent call last)
<ipython-input-16-29eef80a8637> in <module>
1 model = Sequential()
----> 2 model.add(LSTM(units=96, return_sequences=True, input_shape=(x_train.shape[1], 1)))
3 model.add(Dropout(0.2))
4 model.add(LSTM(units=96,return_sequences=True))
5 model.add(Dropout(0.2))
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/training/tracking/base.py in _method_wrapper(self, *args, **kwargs)
520 self._self_setattr_tracking = False # pylint: disable=protected-access
521 try:
--> 522 result = method(self, *args, **kwargs)
523 finally:
524 self._self_setattr_tracking = previous_value # pylint: disable=protected-access
~/anaconda3/lib/python3.8/site-packages/keras/engine/sequential.py in add(self, layer)
206 # and create the node connecting the current layer
207 # to the input layer we just created.
--> 208 layer(x)
209 set_inputs = True
210
~/anaconda3/lib/python3.8/site-packages/keras/layers/recurrent.py in __call__(self, inputs, initial_state, constants, **kwargs)
658
659 if initial_state is None and constants is None:
--> 660 return super(RNN, self).__call__(inputs, **kwargs)
661
662 # If any of `initial_state` or `constants` are specified and are Keras
~/anaconda3/lib/python3.8/site-packages/keras/engine/base_layer.py in __call__(self, *args, **kwargs)
943 # >> model = tf.keras.Model(inputs, outputs)
944 if _in_functional_construction_mode(self, inputs, args, kwargs, input_list):
--> 945 return self._functional_construction_call(inputs, args, kwargs,
946 input_list)
947
~/anaconda3/lib/python3.8/site-packages/keras/engine/base_layer.py in _functional_construction_call(self, inputs, args, kwargs, input_list)
1081 layer=self, inputs=inputs, build_graph=True, training=training_value):
1082 # Check input assumptions set after layer building, e.g. input shape.
-> 1083 outputs = self._keras_tensor_symbolic_call(
1084 inputs, input_masks, args, kwargs)
1085
~/anaconda3/lib/python3.8/site-packages/keras/engine/base_layer.py in _keras_tensor_symbolic_call(self, inputs, input_masks, args, kwargs)
814 return tf.nest.map_structure(keras_tensor.KerasTensor, output_signature)
815 else:
--> 816 return self._infer_output_signature(inputs, args, kwargs, input_masks)
817
818 def _infer_output_signature(self, inputs, args, kwargs, input_masks):
~/anaconda3/lib/python3.8/site-packages/keras/engine/base_layer.py in _infer_output_signature(self, inputs, args, kwargs, input_masks)
854 self._maybe_build(inputs)
855 inputs = self._maybe_cast_inputs(inputs)
--> 856 outputs = call_fn(inputs, *args, **kwargs)
857
858 self._handle_activity_regularization(inputs, outputs)
~/anaconda3/lib/python3.8/site-packages/keras/layers/recurrent_v2.py in call(self, inputs, mask, training, initial_state)
1137
1138 # LSTM does not support constants. Ignore it during process.
-> 1139 inputs, initial_state, _ = self._process_inputs(inputs, initial_state, None)
1140
1141 if isinstance(mask, list):
~/anaconda3/lib/python3.8/site-packages/keras/layers/recurrent.py in _process_inputs(self, inputs, initial_state, constants)
858 initial_state = self.states
859 elif initial_state is None:
--> 860 initial_state = self.get_initial_state(inputs)
861
862 if len(initial_state) != len(self.states):
~/anaconda3/lib/python3.8/site-packages/keras/layers/recurrent.py in get_initial_state(self, inputs)
640 dtype = inputs.dtype
641 if get_initial_state_fn:
--> 642 init_state = get_initial_state_fn(
643 inputs=None, batch_size=batch_size, dtype=dtype)
644 else:
~/anaconda3/lib/python3.8/site-packages/keras/layers/recurrent.py in get_initial_state(self, inputs, batch_size, dtype)
2506
2507 def get_initial_state(self, inputs=None, batch_size=None, dtype=None):
-> 2508 return list(_generate_zero_filled_state_for_cell(
2509 self, inputs, batch_size, dtype))
2510
~/anaconda3/lib/python3.8/site-packages/keras/layers/recurrent.py in _generate_zero_filled_state_for_cell(cell, inputs, batch_size, dtype)
2988 batch_size = tf.compat.v1.shape(inputs)[0]
2989 dtype = inputs.dtype
-> 2990 return _generate_zero_filled_state(batch_size, cell.state_size, dtype)
2991
2992
~/anaconda3/lib/python3.8/site-packages/keras/layers/recurrent.py in _generate_zero_filled_state(batch_size_tensor, state_size, dtype)
3004
3005 if tf.nest.is_nested(state_size):
-> 3006 return tf.nest.map_structure(create_zeros, state_size)
3007 else:
3008 return create_zeros(state_size)
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/util/nest.py in map_structure(func, *structure, **kwargs)
865
866 return pack_sequence_as(
--> 867 structure[0], [func(*x) for x in entries],
868 expand_composites=expand_composites)
869
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/util/nest.py in <listcomp>(.0)
865
866 return pack_sequence_as(
--> 867 structure[0], [func(*x) for x in entries],
868 expand_composites=expand_composites)
869
~/anaconda3/lib/python3.8/site-packages/keras/layers/recurrent.py in create_zeros(unnested_state_size)
3001 flat_dims = tf.TensorShape(unnested_state_size).as_list()
3002 init_state_size = [batch_size_tensor] + flat_dims
-> 3003 return tf.zeros(init_state_size, dtype=dtype)
3004
3005 if tf.nest.is_nested(state_size):
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py in wrapper(*args, **kwargs)
204 """Call target, and fall back on dispatchers if there is a TypeError."""
205 try:
--> 206 return target(*args, **kwargs)
207 except (TypeError, ValueError):
208 # Note: convert_to_eager_tensor currently raises a ValueError, not a
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/array_ops.py in wrapped(*args, **kwargs)
2909
2910 def wrapped(*args, **kwargs):
-> 2911 tensor = fun(*args, **kwargs)
2912 tensor._is_zeros_tensor = True
2913 return tensor
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/array_ops.py in zeros(shape, dtype, name)
2958 # Create a constant if it won't be very big. Otherwise create a fill
2959 # op to prevent serialized GraphDefs from becoming too large.
-> 2960 output = _constant_if_small(zero, shape, dtype, name)
2961 if output is not None:
2962 return output
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/array_ops.py in _constant_if_small(value, shape, dtype, name)
2894 def _constant_if_small(value, shape, dtype, name):
2895 try:
-> 2896 if np.prod(shape) < 1000:
2897 return constant(value, shape=shape, dtype=dtype, name=name)
2898 except TypeError:
<__array_function__ internals> in prod(*args, **kwargs)
~/anaconda3/lib/python3.8/site-packages/numpy/core/fromnumeric.py in prod(a, axis, dtype, out, keepdims, initial, where)
3028 10
3029 """
-> 3030 return _wrapreduction(a, np.multiply, 'prod', axis, dtype, out,
3031 keepdims=keepdims, initial=initial, where=where)
3032
~/anaconda3/lib/python3.8/site-packages/numpy/core/fromnumeric.py in _wrapreduction(obj, ufunc, method, axis, dtype, out, **kwargs)
85 return reduction(axis=axis, out=out, **passkwargs)
86
---> 87 return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
88
89
~/anaconda3/lib/python3.8/site-packages/tensorflow/python/framework/ops.py in __array__(self)
865
866 def __array__(self):
--> 867 raise NotImplementedError(
868 "Cannot convert a symbolic Tensor ({}) to a numpy array."
869 " This error may indicate that you're trying to pass a Tensor to"
NotImplementedError: Cannot convert a symbolic Tensor (lstm_1/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```
This is not "fixed" by downgrading your whole Python or numpy installation - other libraries depend on having an up-to-date version of numpy installed (pandas-ta being one of them). numpy 1.20 is now half a year old and Tensorflow should start supporting it.
i was able to fix issue
Go to C:\Users\khana\miniconda3\envs\tutorialenv\Lib\site-packages\tensorflow\python\ops\array_ops.py
Add - from tensorflow.python.ops.math_ops import reduce_prod
Change to this def _constant_if_small(value, shape, dtype, name): try: if reduce_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
tensorflow - 2.5.0 python - 3.7.0
