UNIMPLEMENTED: DNN library is not found. #10590

MarkosMuche · 2022-04-12T23:12:54Z

I was following the movinet transfer learning tutorial: https://github.com/tensorflow/models/blob/master/official/projects/movinet/movinet_tutorial.ipynb
I downloaded it, uploaded it to colab and run it. I am encountering the problem "UNIMPLEMENTED: DNN library is not found." It doesn't run on GPU.

  return conv_fn(inputs)

Node: 'movinet_classifier_1/movinet/stem/stem/conv3d/StatefulPartitionedCall'
Failed to determine best cudnn convolution algorithm for:
%cudnn-conv = (f32[8,8,86,86,8]{3,2,1,4,0}, u8[0]{0}) custom-call(f32[8,8,173,173,3]{3,2,1,4,0} %pad, f32[1,3,3,3,8]{2,1,0,3,4} %copy.1), window={size=1x3x3 stride=1x2x2}, dim_labels=b012f_012io->b012f, custom_call_target="__cudnn$convForward", metadata={op_type="Conv3D" op_name="Conv3D" source_file="/usr/local/lib/python3.7/dist-packages/keras/layers/convolutional/base_conv.py" source_line=232}, backend_config="{"conv_result_scale":1,"activation_mode":"0","side_input_scale":0}"

Original error: UNIMPLEMENTED: DNN library is not found.

To ignore this failure and try to use a fallback algorithm (which may have suboptimal performance), use XLA_FLAGS=--xla_gpu_strict_conv_algorithm_picker=false. Please also file a bug for the root cause of failing autotuning.
[[{{node movinet_classifier_1/movinet/stem/stem/conv3d/StatefulPartitionedCall}}]] [Op:__inference_train_function_104591]

Solution found:

@MMBB7 followed the instructions on googlecolab/colabtools#2600 and used:

factory reset runtime in colab runtime
!pip install tensorflow==2.8
!apt install --allow-change-held-packages libcudnn8=8.1.0.77-1+cuda11.2

The text was updated successfully, but these errors were encountered:

saberkun · 2022-04-13T03:00:56Z

This is a strange error related to XLA gpu? @cheshire could you help take a look?

cheshire · 2022-04-13T13:29:38Z

@saberkun this is a cuDNN error, which is used for convolutions in both TF and XLA, it's not specific to XLA:GPU in any way. Probably cuDNN is not linked properly.

pindinagesh · 2022-04-13T13:32:49Z

Hi @MarkosMuche

Can you take a look at the workaround proposed in this link and see if it helps in resolving your issue? Thanks!

MarkosMuche · 2022-04-13T15:57:59Z

@pindinagesh I tried it; however It is throwing another error. AssertionError: Duplicate registrations for type 'experimentalOptimizer' . I searched for solutions and found out that it is tensorflow and keras version.
I think this is a different issue, I will see if I can fix it.

MarkosMuche · 2022-04-14T05:36:40Z

unfortunately, the above issue (tensorflow keras compatibility) couldn't be solved. Is there any other way to solve the DLL issue without going back to tensorflow 2.7?

saberkun · 2022-04-15T03:04:19Z

Can you make sure the keras version is also 2.8? For keras experimental optimizer issue, @chenmoneygithub

MMBB7 · 2022-04-20T19:40:35Z

I am having the same issue, has there been a resolution? The CNN model runs in jupyter notebook but not in colab.

saberkun · 2022-04-20T20:20:03Z

What's the tensorflow version and cuda used by the colab runtime?
It does not look like a model code error. We probably need TF team to inspect. Do you mind open such issue in tensorflow github for TF team to take a look?

saberkun · 2022-04-20T22:21:35Z

@mihaimaruseac

MMBB7 · 2022-04-20T23:34:12Z

Hi Saberkun,
My apologies, I should have posted this sooner

I followed the instructions on googlecolab/colabtools#2600 and used:

factory reset runtime in colab runtime
!pip install tensorflow==2.8
!apt install --allow-change-held-packages libcudnn8=8.1.0.77-1+cuda11.2

and this resolved the issue.
Many thanks

saberkun · 2022-04-21T16:29:21Z

@MMBB7 thank you very much! Let's highlight the solution you found.

google-ml-butler · 2022-04-22T03:09:11Z

Are you satisfied with the resolution of your issue?
Yes
No

Waterkin · 2022-05-14T02:36:52Z

under cuda 11.2 install cudnn>8.2
https://stackoverflow.com/questions/55256671/how-to-install-latest-cudnn-to-conda

IamNaQi · 2022-05-29T16:41:51Z

@MMBB7 thank you .. this worked for me

mahmudtolba · 2022-06-13T09:22:14Z

that worked

cosmo3769 · 2022-07-26T09:52:48Z

Hi Saberkun, My apologies, I should have posted this sooner

I followed the instructions on googlecolab/colabtools#2600 and used:

factory reset runtime in colab runtime

!pip install tensorflow==2.8

!apt install --allow-change-held-packages libcudnn8=8.1.0.77-1+cuda11.2

and this resolved the issue. Many thanks

Hi @MMBB7

As I am using kerasCV for augmentation, it needs Tensorflow 2.9+ version, so switching to Tensorflow 2.8 will not work in my use case. Any workaround or solution for this?

arghanath007 · 2022-08-18T03:47:00Z

What is the issue? I am running the models on Google Colab. Yesterday it was running/working fine but today I am running the notebooks, it is giving me this error.
Detected at node 'model/efficientnetv2-b0/stem_conv/Conv2D' defined at (most recent call last): File "/usr/lib/python3.7/runpy.py", line 193, in _run_module_as_main "__main__", mod_spec) File "/usr/lib/python3.7/runpy.py", line 85, in _run_code exec(code, run_globals) File "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py", line 16, in <module> app.launch_new_instance() File "/usr/local/lib/python3.7/dist-packages/traitlets/config/application.py", line 846, in launch_instance app.start() File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelapp.py", line 612, in start self.io_loop.start() File "/usr/local/lib/python3.7/dist-packages/tornado/platform/asyncio.py", line 132, in start self.asyncio_loop.run_forever() File "/usr/lib/python3.7/asyncio/base_events.py", line 541, in run_forever self._run_once() File "/usr/lib/python3.7/asyncio/base_events.py", line 1786, in _run_once handle._run() File "/usr/lib/python3.7/asyncio/events.py", line 88, in _run self._context.run(self._callback, *self._args) File "/usr/local/lib/python3.7/dist-packages/tornado/ioloop.py", line 758, in _run_callback ret = callback() File "/usr/local/lib/python3.7/dist-packages/tornado/stack_context.py", line 300, in null_wrapper return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 1233, in inner self.run() File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 1147, in run yielded = self.gen.send(value) File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 381, in dispatch_queue yield self.process_one() File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 346, in wrapper runner = Runner(result, future, yielded) File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 1080, in __init__ self.run() File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 1147, in run yielded = self.gen.send(value) File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 365, in process_one yield gen.maybe_future(dispatch(*args)) File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 326, in wrapper yielded = next(result) File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 268, in dispatch_shell yield gen.maybe_future(handler(stream, idents, msg)) File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 326, in wrapper yielded = next(result) File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 545, in execute_request user_expressions, allow_stdin, File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 326, in wrapper yielded = next(result) File "/usr/local/lib/python3.7/dist-packages/ipykernel/ipkernel.py", line 306, in do_execute res = shell.run_cell(code, store_history=store_history, silent=silent) File "/usr/local/lib/python3.7/dist-packages/ipykernel/zmqshell.py", line 536, in run_cell return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2855, in run_cell raw_cell, store_history, silent, shell_futures) File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2881, in _run_cell return runner(coro) File "/usr/local/lib/python3.7/dist-packages/IPython/core/async_helpers.py", line 68, in _pseudo_sync_runner coro.send(None) File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 3058, in run_cell_async interactivity=interactivity, compiler=compiler, result=result) File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 3249, in run_ast_nodes if (await self.run_code(code, result, async_=asy)): File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 3326, in run_code exec(code_obj, self.user_global_ns, self.user_ns) File "<ipython-input-30-4999ceb7efa4>", line 1, in <module> history_101_food_classes_feature_extract = model.fit(train_data, epochs=10,steps_per_epoch=len(train_data), validation_data=test_data, validation_steps=int(0.15 * len(test_data)),callbacks=[tensorboard_callback, checkpoint_callback, lr_scheduler_callback, learning_rate_reduce_callback]) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1409, in fit tmp_logs = self.train_function(iterator) File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1051, in train_function return step_function(self, iterator) File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1040, in step_function outputs = model.distribute_strategy.run(run_step, args=(data,)) File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1030, in run_step outputs = model.train_step(data) File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 889, in train_step y_pred = self(x, training=True) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 490, in __call__ return super().__call__(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/engine/base_layer.py", line 1014, in __call__ outputs = call_fn(inputs, *args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 92, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/engine/functional.py", line 459, in call inputs, training=training, mask=mask) File "/usr/local/lib/python3.7/dist-packages/keras/engine/functional.py", line 596, in _run_internal_graph outputs = node.layer(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 490, in __call__ return super().__call__(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/engine/base_layer.py", line 1014, in __call__ outputs = call_fn(inputs, *args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 92, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/engine/functional.py", line 459, in call inputs, training=training, mask=mask) File "/usr/local/lib/python3.7/dist-packages/keras/engine/functional.py", line 596, in _run_internal_graph outputs = node.layer(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/engine/base_layer.py", line 1014, in __call__ outputs = call_fn(inputs, *args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 92, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/layers/convolutional/base_conv.py", line 250, in call outputs = self.convolution_op(inputs, self.kernel) File "/usr/local/lib/python3.7/dist-packages/keras/layers/convolutional/base_conv.py", line 232, in convolution_op name=self.__class__.__name__) Node: 'model/efficientnetv2-b0/stem_conv/Conv2D' DNN library is not found. [[{{node model/efficientnetv2-b0/stem_conv/Conv2D}}]] [Op:__inference_train_function_18869]

MarkosMuche · 2022-08-18T04:37:46Z

Hi Saberkun, My apologies, I should have posted this sooner

I followed the instructions on googlecolab/colabtools#2600 and used:

factory reset runtime in colab runtime

!pip install tensorflow==2.8

!apt install --allow-change-held-packages libcudnn8=8.1.0.77-1+cuda11.2

and this resolved the issue. Many thanks

Number 3, solved my issue, thanks.

MarkosMuche · 2022-08-18T04:39:38Z

What is the issue? I am running the models on Google Colab. Yesterday it was running/working fine but today I am running the notebooks, it is giving me this error. Detected at node 'model/efficientnetv2-b0/stem_conv/Conv2D' defined at (most recent call last): File "/usr/lib/python3.7/runpy.py", line 193, in _run_module_as_main "__main__", mod_spec) File "/usr/lib/python3.7/runpy.py", line 85, in _run_code exec(code, run_globals) File "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py", line 16, in <module> app.launch_new_instance() File "/usr/local/lib/python3.7/dist-packages/traitlets/config/application.py", line 846, in launch_instance app.start() File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelapp.py", line 612, in start self.io_loop.start() File "/usr/local/lib/python3.7/dist-packages/tornado/platform/asyncio.py", line 132, in start self.asyncio_loop.run_forever() File "/usr/lib/python3.7/asyncio/base_events.py", line 541, in run_forever self._run_once() File "/usr/lib/python3.7/asyncio/base_events.py", line 1786, in _run_once handle._run() File "/usr/lib/python3.7/asyncio/events.py", line 88, in _run self._context.run(self._callback, *self._args) File "/usr/local/lib/python3.7/dist-packages/tornado/ioloop.py", line 758, in _run_callback ret = callback() File "/usr/local/lib/python3.7/dist-packages/tornado/stack_context.py", line 300, in null_wrapper return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 1233, in inner self.run() File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 1147, in run yielded = self.gen.send(value) File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 381, in dispatch_queue yield self.process_one() File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 346, in wrapper runner = Runner(result, future, yielded) File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 1080, in __init__ self.run() File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 1147, in run yielded = self.gen.send(value) File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 365, in process_one yield gen.maybe_future(dispatch(*args)) File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 326, in wrapper yielded = next(result) File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 268, in dispatch_shell yield gen.maybe_future(handler(stream, idents, msg)) File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 326, in wrapper yielded = next(result) File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 545, in execute_request user_expressions, allow_stdin, File "/usr/local/lib/python3.7/dist-packages/tornado/gen.py", line 326, in wrapper yielded = next(result) File "/usr/local/lib/python3.7/dist-packages/ipykernel/ipkernel.py", line 306, in do_execute res = shell.run_cell(code, store_history=store_history, silent=silent) File "/usr/local/lib/python3.7/dist-packages/ipykernel/zmqshell.py", line 536, in run_cell return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2855, in run_cell raw_cell, store_history, silent, shell_futures) File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2881, in _run_cell return runner(coro) File "/usr/local/lib/python3.7/dist-packages/IPython/core/async_helpers.py", line 68, in _pseudo_sync_runner coro.send(None) File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 3058, in run_cell_async interactivity=interactivity, compiler=compiler, result=result) File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 3249, in run_ast_nodes if (await self.run_code(code, result, async_=asy)): File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 3326, in run_code exec(code_obj, self.user_global_ns, self.user_ns) File "<ipython-input-30-4999ceb7efa4>", line 1, in <module> history_101_food_classes_feature_extract = model.fit(train_data, epochs=10,steps_per_epoch=len(train_data), validation_data=test_data, validation_steps=int(0.15 * len(test_data)),callbacks=[tensorboard_callback, checkpoint_callback, lr_scheduler_callback, learning_rate_reduce_callback]) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1409, in fit tmp_logs = self.train_function(iterator) File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1051, in train_function return step_function(self, iterator) File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1040, in step_function outputs = model.distribute_strategy.run(run_step, args=(data,)) File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1030, in run_step outputs = model.train_step(data) File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 889, in train_step y_pred = self(x, training=True) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 490, in __call__ return super().__call__(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/engine/base_layer.py", line 1014, in __call__ outputs = call_fn(inputs, *args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 92, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/engine/functional.py", line 459, in call inputs, training=training, mask=mask) File "/usr/local/lib/python3.7/dist-packages/keras/engine/functional.py", line 596, in _run_internal_graph outputs = node.layer(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 490, in __call__ return super().__call__(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/engine/base_layer.py", line 1014, in __call__ outputs = call_fn(inputs, *args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 92, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/engine/functional.py", line 459, in call inputs, training=training, mask=mask) File "/usr/local/lib/python3.7/dist-packages/keras/engine/functional.py", line 596, in _run_internal_graph outputs = node.layer(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/engine/base_layer.py", line 1014, in __call__ outputs = call_fn(inputs, *args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 92, in error_handler return fn(*args, **kwargs) File "/usr/local/lib/python3.7/dist-packages/keras/layers/convolutional/base_conv.py", line 250, in call outputs = self.convolution_op(inputs, self.kernel) File "/usr/local/lib/python3.7/dist-packages/keras/layers/convolutional/base_conv.py", line 232, in convolution_op name=self.__class__.__name__) Node: 'model/efficientnetv2-b0/stem_conv/Conv2D' DNN library is not found. [[{{node model/efficientnetv2-b0/stem_conv/Conv2D}}]] [Op:__inference_train_function_18869]

!apt install --allow-change-held-packages libcudnn8=8.1.0.77-1+cuda11.2
The answer by @cosmo3769 worked for me. You create a new cell above and run this piece of command.

arghanath007 · 2022-08-18T05:10:01Z

!apt install --allow-change-held-packages libcudnn8=8.1.0.77-1+cuda11.2 The answer by @cosmo3769 worked for me. You create a new cell above and run this piece of command.

Thanks it solved the error.

kubikub · 2022-08-18T08:17:18Z

!apt install --allow-change-held-packages libcudnn8=8.1.0.77-1+cuda11.2 The answer by @cosmo3769 worked for me. You create a new cell above and run this piece of command.

It works for me too ! thx

MarkosMuche · 2022-08-18T12:47:38Z

Great.

Dreamcouple · 2022-08-22T09:36:10Z

Hi Saberkun, My apologies, I should have posted this sooner

I followed the instructions on googlecolab/colabtools#2600 and used:

factory reset runtime in colab runtime

!pip install tensorflow==2.8

!apt install --allow-change-held-packages libcudnn8=8.1.0.77-1+cuda11.2

and this resolved the issue. Many thanks

how can i install this for pip packages , bcz i have same error in jupyter notebook

MittalNeha · 2022-09-21T11:30:04Z

Hi Saberkun, My apologies, I should have posted this sooner

I followed the instructions on googlecolab/colabtools#2600 and used:

factory reset runtime in colab runtime

!pip install tensorflow==2.8

!apt install --allow-change-held-packages libcudnn8=8.1.0.77-1+cuda11.2

and this resolved the issue. Many thanks

This is the correct solution however I had to add

# Check libcudnn8 version
!apt-cache policy libcudnn8

to get this to work. Also I did not touch the tensorflow installation. only the install and PATH changes related to libcudnn
Reference link:
https://stackoverflow.com/questions/71000120/colab-0-unimplemented-dnn-library-is-not-found

Hope this is helpful to other struggling with this issue.

MarkosMuche added the type:support label Apr 12, 2022

MarkosMuche changed the title ~~UNIMPLEMENTED: DNN library is not found.~~ UNIMPLEMENTED: DNN library is not found. Apr 12, 2022

pindinagesh self-assigned this Apr 13, 2022

pindinagesh added the models:official models that come under official repository label Apr 13, 2022

pindinagesh added the stat:awaiting response Waiting on input from the contributor label Apr 13, 2022

pindinagesh removed the stat:awaiting response Waiting on input from the contributor label Apr 14, 2022

saberkun unassigned pindinagesh Apr 15, 2022

saberkun closed this as completed Apr 22, 2022

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ShiftViT Example Enhancements keras-team/keras-io#1011

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arghanath007 mentioned this issue Aug 18, 2022

Food Vision not training mrdbourke/tensorflow-deep-learning#432

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cosmo3769 mentioned this issue Sep 24, 2022

KerasCV implementation cosmo3769/SSL-study#30

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AmosChenYQ mentioned this issue Nov 11, 2022

XlaRuntimeError: UNKNOWN: Failed to determine best cudnn convolution algorithm for tensorflow/tensorflow#58534

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[TF2 r2.6.0] Train and Eval Model: resnet_rs_imagenet but "RuntimeError: The loss value is NaN" occurs #11121

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UNIMPLEMENTED: DNN library is not found. #10590

UNIMPLEMENTED: DNN library is not found. #10590

MarkosMuche commented Apr 12, 2022 •

edited by saberkun

saberkun commented Apr 13, 2022

cheshire commented Apr 13, 2022 •

edited

pindinagesh commented Apr 13, 2022

MarkosMuche commented Apr 13, 2022 •

edited

MarkosMuche commented Apr 14, 2022

saberkun commented Apr 15, 2022

MMBB7 commented Apr 20, 2022

saberkun commented Apr 20, 2022

saberkun commented Apr 20, 2022

MMBB7 commented Apr 20, 2022

saberkun commented Apr 21, 2022

google-ml-butler bot commented Apr 22, 2022

Waterkin commented May 14, 2022

IamNaQi commented May 29, 2022

mahmudtolba commented Jun 13, 2022

cosmo3769 commented Jul 26, 2022

arghanath007 commented Aug 18, 2022

MarkosMuche commented Aug 18, 2022

MarkosMuche commented Aug 18, 2022

arghanath007 commented Aug 18, 2022 •

edited

kubikub commented Aug 18, 2022 •

edited

MarkosMuche commented Aug 18, 2022

Dreamcouple commented Aug 22, 2022

MittalNeha commented Sep 21, 2022

UNIMPLEMENTED: DNN library is not found. #10590

UNIMPLEMENTED: DNN library is not found. #10590

Comments

MarkosMuche commented Apr 12, 2022 • edited by saberkun

saberkun commented Apr 13, 2022

cheshire commented Apr 13, 2022 • edited

pindinagesh commented Apr 13, 2022

MarkosMuche commented Apr 13, 2022 • edited

MarkosMuche commented Apr 14, 2022

saberkun commented Apr 15, 2022

MMBB7 commented Apr 20, 2022

saberkun commented Apr 20, 2022

saberkun commented Apr 20, 2022

MMBB7 commented Apr 20, 2022

saberkun commented Apr 21, 2022

google-ml-butler bot commented Apr 22, 2022

Waterkin commented May 14, 2022

IamNaQi commented May 29, 2022

mahmudtolba commented Jun 13, 2022

cosmo3769 commented Jul 26, 2022

arghanath007 commented Aug 18, 2022

MarkosMuche commented Aug 18, 2022

MarkosMuche commented Aug 18, 2022

arghanath007 commented Aug 18, 2022 • edited

Thanks it solved the error.

kubikub commented Aug 18, 2022 • edited

MarkosMuche commented Aug 18, 2022

Dreamcouple commented Aug 22, 2022

MittalNeha commented Sep 21, 2022

MarkosMuche commented Apr 12, 2022 •

edited by saberkun

cheshire commented Apr 13, 2022 •

edited

MarkosMuche commented Apr 13, 2022 •

edited

arghanath007 commented Aug 18, 2022 •

edited

kubikub commented Aug 18, 2022 •

edited